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| import openai | |
| import pinecone | |
| import gradio as gr | |
| import os | |
| import json | |
| # initiates pinecone | |
| def init_pinecone(apikey, environment): | |
| pinecone.init(api_key=apikey, environment=environment) | |
| def qa_gita(query, openaikey): | |
| # Basic Checks | |
| if not query: | |
| return "Please enter your query." | |
| if not openaikey: | |
| return "Please enter openaikey." | |
| openai.api_key = openaikey | |
| response = openai.Embedding.create( | |
| input=[query], model="text-embedding-ada-002") | |
| embedding = response["data"][0]["embedding"] | |
| pinecone_api_key_gita = os.getenv("PINECONE_API_KEY_GITA") | |
| pinecone_environment = os.getenv("PINECONE_ENVIRONMENT_GITA") | |
| init_pinecone(pinecone_api_key_gita, pinecone_environment) | |
| index = pinecone.Index("gita") | |
| with open("data.json", "r") as f: | |
| data = json.loads(f.read()) | |
| res = index.query(vector=(embedding), top_k=8) | |
| ids = [i["id"] for i in res["matches"]] | |
| context = "" | |
| for id in ids: | |
| context = context + str(id) + ": " + data["gita"][str(id)] + "\n\n" | |
| systemprompt = f"You are not an AI Language model. You will be a Bhagwad Gita Assistant to the user. Restrict Yourself to the context of the question." | |
| userprompt = f"Verses:\n\n{context}\n\nQuestion: {query}\n\nAnswer:\n\n" | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": systemprompt}, | |
| {"role": "user", "content": userprompt}, | |
| ], | |
| max_tokens=256, | |
| temperature=0.0, | |
| ) | |
| answer = response["choices"][0]["message"]["content"] | |
| return answer, context | |
| def qa_bible(query, openaikey): | |
| # Basic Checks | |
| if not query: | |
| return "Please enter your query." | |
| if not openaikey: | |
| return "Please enter openaikey." | |
| openai.api_key = openaikey | |
| response = openai.Embedding.create( | |
| input=[query], model="text-embedding-ada-002") | |
| embedding = response["data"][0]["embedding"] | |
| pinecone_api_key_bible = os.getenv("PINECONE_API_KEY_BIBLE") | |
| pinecone_environment = os.getenv("PINECONE_ENVIRONMENT_BIBLE") | |
| init_pinecone(pinecone_api_key_bible, pinecone_environment) | |
| index = pinecone.Index("bible") | |
| with open("data.json", "r") as f: | |
| data = json.loads(f.read()) | |
| res = index.query(vector=(embedding), top_k=8) | |
| ids = [i["id"] for i in res["matches"]] | |
| context = "" | |
| for id in ids: | |
| context = context + str(id) + ": " + data["bible"][str(id)] + "\n\n" | |
| systemprompt = f"You are not an AI Language model. You will be a Bible Assistant to the user. Restrict Yourself to the context of the question." | |
| userprompt = f"Verses:\n\n{context}\n\nQuestion: {query}\n\nAnswer:\n\n" | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": systemprompt}, | |
| {"role": "user", "content": userprompt}, | |
| ], | |
| max_tokens=256, | |
| temperature=0.0, | |
| ) | |
| answer = response["choices"][0]["message"]["content"] | |
| return answer, context | |
| def qa_quran(query, openaikey): | |
| # Basic Checks | |
| if not query: | |
| return "Please enter your query." | |
| if not openaikey: | |
| return "Please enter openaikey." | |
| openai.api_key = openaikey | |
| response = openai.Embedding.create( | |
| input=[query], model="text-embedding-ada-002") | |
| embedding = response["data"][0]["embedding"] | |
| pinecone_api_key_quran = os.getenv("PINECONE_API_KEY_QURAN") | |
| pinecone_environment = os.getenv("PINECONE_ENVIRONMENT_QURAN") | |
| init_pinecone(pinecone_api_key_quran, pinecone_environment) | |
| index = pinecone.Index("quran") | |
| with open("data.json", "r") as f: | |
| data = json.loads(f.read()) | |
| res = index.query(vector=(embedding), top_k=8) | |
| ids = [i["id"] for i in res["matches"]] | |
| context = "" | |
| for id in ids: | |
| context = context + str(id) + ": " + data["quran"][str(id)] + "\n\n" | |
| systemprompt = f"You are not an AI Language model. You will be a Quran Assistant to the user. Restrict Yourself to the context of the question." | |
| userprompt = f"Verses:\n\n{context}\n\nQuestion: {query}\n\nAnswer:\n\n" | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": systemprompt}, | |
| {"role": "user", "content": userprompt}, | |
| ], | |
| max_tokens=256, | |
| temperature=0.0, | |
| ) | |
| answer = response["choices"][0]["message"]["content"] | |
| return answer, context | |
| def cleartext(query, output, references): | |
| """ | |
| Function to clear text | |
| """ | |
| return ["", "", ""] | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| <h1><center><b>HolyBot</center></h1> | |
| """ | |
| ) | |
| gr.Markdown( | |
| """ | |
| HolyBot answers your queries and gives relevant verses based on Bhagwad Gita/ Quran/ Bible holy books, built using OpenAI ChatGPT, and Pinecone Index. | |
| - Get your [OpenAI API Key](https://platform.openai.com/account/api-keys) before proceeding further. | |
| - Refer to the codebase for this project on [GitHub](https://github.com/ravi03071991/HolyBot).""" | |
| ) | |
| with gr.Tabs(): | |
| openaikey = gr.Textbox(lines=1, label="Enter Your OpenAI Key") | |
| with gr.TabItem("Bhagwad Gita"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| query1 = gr.Textbox( | |
| lines=2, label="Enter Your Situation/ Query.") | |
| submit_button1 = gr.Button("Submit") | |
| with gr.Column(): | |
| ans_output1 = gr.Textbox(lines=5, label="Answer.") | |
| references1 = gr.Textbox( | |
| lines=10, label="Relevant Verses.") | |
| clear_button1 = gr.Button("Clear") | |
| with gr.TabItem("Quran"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| query2 = gr.Textbox( | |
| lines=2, label="Enter Your Situation/ Query.") | |
| submit_button2 = gr.Button("Submit") | |
| with gr.Column(): | |
| ans_output2 = gr.Textbox(lines=5, label="Answer.") | |
| references2 = gr.Textbox( | |
| lines=10, label="Relevant Verses.") | |
| clear_button2 = gr.Button("Clear") | |
| with gr.TabItem("Bible"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| query3 = gr.Textbox( | |
| lines=2, label="Enter Your Situation/ Query.") | |
| submit_button3 = gr.Button("Submit") | |
| with gr.Column(): | |
| ans_output3 = gr.Textbox(lines=5, label="Answer.") | |
| references3 = gr.Textbox( | |
| lines=10, label="Relevant Verses.") | |
| clear_button3 = gr.Button("Clear") | |
| # For Bhagwad Gita | |
| # Submit button for submitting query. | |
| submit_button1.click(qa_gita, inputs=[query1, openaikey], outputs=[ | |
| ans_output1, references1]) | |
| # Clear button for clearing query and answer. | |
| clear_button1.click( | |
| cleartext, | |
| inputs=[query1, ans_output1, references1], | |
| outputs=[query1, ans_output1, references1], | |
| ) | |
| # For Quran | |
| # Submit button for submitting query. | |
| submit_button2.click(qa_quran, inputs=[query2, openaikey], outputs=[ | |
| ans_output2, references2]) | |
| # Clear button for clearing query and answer. | |
| clear_button2.click( | |
| cleartext, | |
| inputs=[query2, ans_output2, references2], | |
| outputs=[query2, ans_output2, references2], | |
| ) | |
| # For Bible | |
| # Submit button for submitting query. | |
| submit_button3.click(qa_bible, inputs=[query3, openaikey], outputs=[ | |
| ans_output3, references3]) | |
| # Clear button for clearing query and answer. | |
| clear_button3.click( | |
| cleartext, | |
| inputs=[query3, ans_output3, references3], | |
| outputs=[query3, ans_output3, references3], | |
| ) | |
| demo.launch(debug=True) | |