Duplicate from stephenmccartney1234/astrobot

.gitattributes

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+Beacon[[:space:]]Household[[:space:]]Dominica.pdf filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+title: Astrobot
+emoji: ⚡
+colorFrom: purple
+colorTo: gray
+sdk: gradio
+sdk_version: 3.27.0
+app_file: app.py
+pinned: false
+duplicated_from: stephenmccartney1234/astrobot
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+from langchain.chat_models import ChatOpenAI
+import gradio as gr
+import sys
+import os
+ 
+os.environ["OPENAI_API_KEY"] = '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'
+
+def construct_index(directory_path):
+    max_input_size = 4096
+    num_outputs = 512
+    max_chunk_overlap = 20
+    chunk_size_limit = 600
+
+    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
+
+    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
+
+    documents = SimpleDirectoryReader(directory_path).load_data()
+
+    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+    index.save_to_disk('index.json')
+
+    return index
+
+def chatbot(input_text):
+    predetermined_text = "I want you to take the statement at the start of this query and first only answer it using information contained in documents in the 'docs' directory."  
+    input_text = input_text + predetermined_text
+    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+    response = index.query(input_text, response_mode="compact")
+    return response.response
+
+
+
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.components.Textbox(lines=7, label="What would you like to know about the project?"),
+                     outputs="text",
+                     title="SAP Project ChatBot")
+
+index = construct_index("docs")
+iface.launch()

requirements.txt

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+gpt_index==0.4.24
+PyPDF2
+transformers
+tokenizers