Upload 6 files

.gitattributes

@@ -33,3 +33,4 @@ 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
+dww_rev_cleaned_persist/vector_store.json filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,100 @@
+from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader, ServiceContext, set_global_service_context, load_index_from_storage, StorageContext, PromptHelper
+from llama_index.llms import OpenAI
+from llama_index.evaluation import ResponseEvaluator
+from langchain.chat_models import ChatOpenAI
+from PyPDF2 import PdfReader
+import gradio as gr
+import sys
+import os
+
+try:
+    from config import OPEN_AI_KEY
+    os.environ["OPENAI_API_KEY"] = OPEN_AI_KEY
+except:
+    pass
+
+# ===============================
+# Settings
+# ===============================
+
+MAX_INPUT_SIZE = 4096
+NUM_OUTPUT = 3072
+CHUNK_OVERLAP_RATIO = 0.15
+CHUNK_SIZE_LIMIT = 1000
+TEMPERATURE = 0.5
+DIRECTORY = 'dww_rev_cleaned'
+DIRECTORY_PERSIST = 'dww_rev_cleaned_persist'
+
+# Define LLM: gpt-3.5-turbo, temp:0.7
+llm = OpenAI(model="gpt-3.5-turbo", temperature=TEMPERATURE, max_tokens=NUM_OUTPUT)
+
+# Define prompt helper
+prompt_helper = PromptHelper(context_window=MAX_INPUT_SIZE, num_output=NUM_OUTPUT, chunk_overlap_ratio=CHUNK_OVERLAP_RATIO, chunk_size_limit=CHUNK_SIZE_LIMIT)
+
+# Set service context
+service_context = ServiceContext.from_defaults(llm=llm, prompt_helper=prompt_helper)
+set_global_service_context(service_context)
+
+
+# ===============================
+# Functions
+# ===============================
+
+def construct_index(directory_path, index_path):
+    
+    if os.listdir(index_path) != []:
+        storage_context = StorageContext.from_defaults(persist_dir=index_path)
+        index = load_index_from_storage(storage_context)
+        return index
+
+    else:
+        # Load in documents
+        documents = SimpleDirectoryReader(directory_path).load_data()
+
+        # Index documents
+        index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context, show_progress=True)
+
+        # Save index
+        index.storage_context.persist(persist_dir=index_path)
+
+        return index
+
+INDEX = construct_index(DIRECTORY, DIRECTORY_PERSIST)
+QE = INDEX.as_query_engine()
+PDF_CONTENT = gr.State("")
+
+def upload_file(file):
+    try:
+        read_pdf = PdfReader(file.name)
+        pdf_text = "\n\n".join([w.extract_text() for w in read_pdf.pages])
+        PDF_CONTENT.value = pdf_text
+        return pdf_text
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def chatfunc(input_text, chat_history, max_chat_length=6):
+    prompt = """You are an insight bot that helps users (special educators and school psychologists) build individual education programs based on disability categories using DWW (a library of research-backed interviews and tools) as reference. 
+                Refer to the DWW's context as much as you can to provide a detailed answer."""
+    if PDF_CONTENT.value:
+        prompt = prompt + "The following is the relevant document provided by the user" + PDF_CONTENT.value + "\n\n"
+    for chat in chat_history[~max_chat_length:]:
+        user_chat, bot_chat = chat
+        prompt = f"{prompt}\nUser: {user_chat}\nAssistant: {bot_chat}"
+    prompt = f"{prompt}\nUser: {input_text}\nAssistant:"
+    response = QE.query(prompt)
+    chat_history.append([input_text, response.response])
+    return "", chat_history
+
+with gr.Blocks() as iface:
+    chatbot = gr.Chatbot(height=400)
+    msg = gr.Textbox(label="Ask the DWW Bot anything about research-based practices in education")
+    submit = gr.Button("💬 Submit")
+    with gr.Row():
+        clear = gr.ClearButton(value="🧹 Clear outputs", components=[msg, chatbot])
+        upload_button = gr.UploadButton("📁 Upload a relevant document", file_types=[".pdf"], file_count="single")
+    with gr.Accordion("📝 View your document"):
+        syl = gr.Textbox(label="Your documents' content will show here")
+    msg.submit(chatfunc, [msg, chatbot], [msg, chatbot])
+    upload_button.upload(upload_file, upload_button, syl)  
+
+iface.launch(share=False)

dww_rev_cleaned_persist/graph_store.json

@@ -0,0 +1 @@
+{"graph_dict": {}}

dww_rev_cleaned_persist/index_store.json

@@ -0,0 +1 @@
+{"index_store/data": {"0dbe18af-b3c3-4371-acf2-4e011ed8d081": {"__type__": "vector_store", "__data__": "{\"index_id\": \"0dbe18af-b3c3-4371-acf2-4e011ed8d081\", \"summary\": null, \"nodes_dict\": {\"6625bad6-e900-4412-8c8d-775bccacf326\": \"6625bad6-e900-4412-8c8d-775bccacf326\", \"2c9ab3f9-371f-42f9-b926-72f3401c9461\": \"2c9ab3f9-371f-42f9-b926-72f3401c9461\", \"69e6f4e0-58be-4002-b6cf-0c81b112b5d4\": \"69e6f4e0-58be-4002-b6cf-0c81b112b5d4\", \"6f0f7809-7d05-47e5-80e7-6d2a0148d887\": \"6f0f7809-7d05-47e5-80e7-6d2a0148d887\", \"fc66633f-9c4e-491d-9697-238b324c4982\": \"fc66633f-9c4e-491d-9697-238b324c4982\", \"ea364d2e-ccde-41d7-a0d5-c028eed83338\": \"ea364d2e-ccde-41d7-a0d5-c028eed83338\", \"bb43dab5-9b43-470d-9aa2-26944205561e\": \"bb43dab5-9b43-470d-9aa2-26944205561e\", \"d400c22b-2fa9-4524-a35c-0e63f343505d\": \"d400c22b-2fa9-4524-a35c-0e63f343505d\", \"b34fb150-89e6-4e0b-91c4-bcfdbb9a4050\": \"b34fb150-89e6-4e0b-91c4-bcfdbb9a4050\", \"19296633-407d-4b62-b2a3-9321448ea99d\": 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dww_rev_cleaned_persist/vector_store.json

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requirements.txt

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