Added files and database

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
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+distilbert/chroma.sqlite3 filter=lfs diff=lfs merge=lfs -text

demo.py

@@ -0,0 +1,116 @@
+import gradio as gr
+
+from dotenv import load_dotenv
+load_dotenv()
+
+# VectorIndexRetriever
+from llama_index.schema import NodeWithScore
+from llama_index import GPTVectorStoreIndex, ServiceContext
+from llama_index.storage import StorageContext
+from llama_index.vector_stores import ChromaVectorStore
+from llama_index.memory import ChatMemoryBuffer
+from llama_index.embeddings import HuggingFaceEmbedding
+
+import chromadb
+
+chroma_client = chromadb.PersistentClient(path="distilbert/")
+
+chroma_collection = chroma_client.get_or_create_collection("distilbert")
+
+vector_store = ChromaVectorStore(chroma_collection=chroma_collection)
+storage_context = StorageContext.from_defaults(vector_store=vector_store)
+embed_model = HuggingFaceEmbedding(model_name="distilbert-base-uncased")
+service_context = ServiceContext.from_defaults(embed_model=embed_model)
+index = GPTVectorStoreIndex.from_vector_store(
+    vector_store=vector_store,
+    storage_context=storage_context,
+    service_context=service_context
+)
+
+memory = ChatMemoryBuffer.from_defaults(token_limit=1000)
+
+chat_engine = index.as_chat_engine(
+    similarity_top_k=5,
+    chat_mode="context",
+    memory=memory,
+    system_prompt="You are an Artificial Intelligence (AI)-powered app called STAR " + \
+                  "(Standards Technical Assistance Resource) that could " + \
+                  "streamline the process and offer requirement " + \
+                  "recommendations, you can be used as copilot, to help " + \
+                  "mission designers blast off with even greater " + \
+                  "confidence, knowing that they have the right " + \
+                  "requirements in place. You should analyze and suggest " + \
+                  "improvements to a NASA standards."
+)
+query_engine = index.as_query_engine()
+retriever = index.as_retriever(
+    similarity_top_k=5,
+)
+
+THRESHOLD = 1e-9
+
+def inference(text, reset):
+    if text:
+        response = chat_engine.chat(text)
+        top_k_similar_nodes = retriever.retrieve(text)
+        to_view = []
+        for node in top_k_similar_nodes:
+            # print(node.get_score(), end = ' ')
+            if node.get_score() > THRESHOLD:
+                to_view.append((node.metadata()['file_name'], node.get_score()))
+            # to_view.append((node.metadata()['file_name'], node.get_score()))
+        references = ""
+        if len(to_view) > 0:
+            for i, t in enumerate(to_view):
+                filename, score = t
+                splits = filename.split('_')
+                page_number = int(splits[1])
+                original_document = ''.join(splits[3:])
+                references += f'{i + 1}- Document: ' + \
+                    f'{original_document[:-4]}, Page: ' + \
+                        f'{page_number} (Score: {score}).'
+                if i != len(to_view) - 1:
+                    references += '\n'
+        if reset:
+            memory.reset()
+        return response, references
+    elif reset:
+        memory.reset()
+    return "", ""
+
+examples = [
+    [
+        "How should the length-to-depth ratio of the initial flaw be " + \
+        "assumed when using the NASGRO® computer program for glass " + \
+        "structure analysis? Please provide a detailed procedure.",
+        True
+    ]
+]
+
+playground = gr.Interface(
+    fn=inference,
+    inputs=[
+        gr.Textbox(
+            value="Hello, who are you?",
+            label="Input",
+            info="Chat with STAR."
+        ),
+        gr.Checkbox(
+            label="Reset chat history",
+            info="Start a new conversation from scratch with STAR."
+        )
+    ],
+    outputs=[
+        gr.Textbox(
+            label="Response"
+        ),
+        gr.Textbox(
+            label="References"
+        )
+    ],
+    examples=examples,
+    cache_examples=True,
+    allow_flagging=False
+)
+
+playground.launch(share=True)

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requirements.txt

@@ -0,0 +1,171 @@
+absl-py==2.0.0
+aiofiles==23.2.1
+aiohttp==3.8.5
+aiosignal==1.3.1
+altair==5.1.2
+annotated-types==0.6.0
+anyio==3.7.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.1.0
+backoff==2.2.1
+bcrypt==4.0.1
+beautifulsoup4==4.12.2
+bs4==0.0.1
+cachetools==5.3.1
+certifi==2023.7.22
+charset-normalizer==3.3.0
+chroma-hnswlib==0.7.3
+chromadb==0.4.13
+click==8.1.7
+coloredlogs==15.0.1
+contourpy==1.1.1
+cycler==0.12.1
+dataclasses-json==0.6.1
+diskcache==5.6.3
+exceptiongroup==1.1.3
+fastapi==0.103.2
+ffmpy==0.3.1
+filelock==3.12.4
+flatbuffers==23.5.26
+fonttools==4.43.1
+frozenlist==1.4.0
+fsspec==2023.9.2
+gast==0.5.4
+google-auth==2.23.2
+google-auth-oauthlib==1.0.0
+google-pasta==0.2.0
+gradio==3.47.1
+gradio_client==0.6.0
+greenlet==3.0.0
+grpcio==1.59.0
+h11==0.14.0
+h5py==3.9.0
+httpcore==0.18.0
+httptools==0.6.0
+httpx==0.25.0
+huggingface-hub==0.17.3
+humanfriendly==10.0
+idna==3.4
+importlib-resources==6.1.0
+Jinja2==3.1.2
+joblib==1.3.2
+jsonpatch==1.33
+jsonpointer==2.4
+jsonschema==4.19.1
+jsonschema-specifications==2023.7.1
+keras==2.14.0
+kiwisolver==1.4.5
+langchain==0.0.310
+langsmith==0.0.43
+libclang==16.0.6
+llama-index==0.8.40
+llama_cpp_python==0.2.11
+Markdown==3.5
+MarkupSafe==2.1.3
+marshmallow==3.20.1
+matplotlib==3.8.0
+ml-dtypes==0.2.0
+monotonic==1.6
+mpmath==1.3.0
+multidict==6.0.4
+mypy-extensions==1.0.0
+nest-asyncio==1.5.8
+networkx==3.1
+nltk==3.8.1
+numpy==1.26.0
+nvidia-cublas-cu11==11.11.3.6
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu11==11.8.87
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvcc-cu11==11.8.89
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+triton==2.1.0
+typer==0.9.0
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+tzdata==2023.3
+urllib3==1.26.17
+uvicorn==0.23.2
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+websockets==11.0.3
+Werkzeug==3.0.0
+wrapt==1.14.1
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