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| import gradio as gr | |
| from gradio_client import Client | |
| import subprocess as sp | |
| import time | |
| import requests | |
| def upload_to_fileio(file_path): | |
| with open(file_path, 'rb') as f: | |
| response = requests.post('https://file.io', files={'file': f}) | |
| if response.status_code == 200: | |
| return response.json().get('link') | |
| else: | |
| return "#" | |
| api_client = Client("eswardivi/Phi-3-mini-128k-instruct") | |
| def blast_search(inputfile, matchesnumber, qcovcutoff, evaluecutoff): | |
| sp.run("echo 'QUERY_SEQ\tTAXON\tQUERY_COVERAGE\tPERC_ID\tLENGTH\tMISMATCHES\tGAPS\tE_VALUE\tBITSCORE' > results.txt", shell=True) | |
| sp.run(f"blastn -query {inputfile} -db 16S_ribosomal_RNA -outfmt '6 qseqid sscinames qcov pident length mismatch gapopen evalue bitscore' -max_target_seqs {matchesnumber} -evalue {evaluecutoff} -qcov_hsp_perc {qcovcutoff} >> results.txt", shell=True) | |
| f = open("results.txt") | |
| content = f.read() | |
| f.close() | |
| link = upload_to_fileio("results.txt") | |
| return content, link | |
| def reply(user_prompt, history, inputfile, matchesnumber, qcovcutoff, evaluecutoff): | |
| context, filelink = blast_search(inputfile, matchesnumber, qcovcutoff, evaluecutoff) | |
| instructions = "You are a helpful assistant whose job is to summarize in a straight-to-the-point but effective way the result of a BLAST search conducted on a 16S rRNA bacterial sequences database from NCBI." | |
| full_prompt = f"{instructions} Based on thr content of this TSV file resulting from a BLAST search: \"\"\"{context}\"\"\", summarize the mentioned output complying with these user-provided instructions: {user_prompt}" | |
| response = api_client.predict( | |
| full_prompt, # str in 'Message' Textbox component | |
| 0.2, # float (numeric value between 0 and 1) in 'Temperature' Slider component | |
| True, # bool in 'Sampling' Checkbox component | |
| 512, # float (numeric value between 128 and 4096) in 'Max new tokens' Slider component | |
| api_name="/chat" | |
| ) | |
| response = response + f"\n\nDownload you BLAST results [at this link]({filelink})" | |
| this_hist = '' | |
| for char in response: | |
| this_hist += char | |
| time.sleep(0.0001) | |
| yield this_hist | |
| def summarize_description_table(description_table_file): | |
| f = open(description_table_file) | |
| lines = f.readlines() | |
| if len(lines) > 10: | |
| incipit = "**⚠️: The number of hits was higher than 10. Only the first 10 hits were taken into account.**\n\n" | |
| lines = lines[:11] | |
| else: | |
| incipit = "" | |
| content = "".join(lines) | |
| return incipit, content | |
| def ai_summarize(user_prompt, history, inputfile): | |
| incipit, context = summarize_description_table(inputfile) | |
| instructions = "You are a helpful assistant whose job is to summarize in a straight-to-the-point but effective way the result of a BLAST search conducted online on NCBI databases." | |
| full_prompt = f"{instructions} Based on thr content of this CSV file resulting from a BLAST search: \"\"\"{context}\"\"\", summarize the mentioned output complying with these user-provided instructions: {user_prompt}" | |
| response = api_client.predict( | |
| full_prompt, # str in 'Message' Textbox component | |
| 0.2, # float (numeric value between 0 and 1) in 'Temperature' Slider component | |
| True, # bool in 'Sampling' Checkbox component | |
| 512, # float (numeric value between 128 and 4096) in 'Max new tokens' Slider component | |
| api_name="/chat" | |
| ) | |
| response = incipit+response | |
| this_hist = '' | |
| for char in response: | |
| this_hist += char | |
| time.sleep(0.0001) | |
| yield this_hist | |
| user_file = gr.File(label="Upload FASTA File") | |
| user_file1 = gr.File(label="Upload Description Table (CSV) Downloadable From Online BLAST Results") | |
| user_max_matches = gr.Slider(5, 50, value=20, label="Max Hits per Sequence", info="Select maximum number of BLAST hits per sequence (higher number of hits will result in a longer latency)") | |
| user_qcov = gr.Slider(0, 100, value=0, label="Minimum Query Coverage", info="Minimum query coverage for a hit to be considered") | |
| user_evalue = gr.Textbox(label="E-value threshold",info="All the hits below the threshold will be considered",value="1e-10") | |
| additional_accordion = gr.Accordion(label="Parameters to be set before you start chatting", open=True) | |
| demo0 = gr.ChatInterface(fn=reply, additional_inputs=[user_file, user_max_matches, user_qcov, user_evalue], additional_inputs_accordion=additional_accordion, title="""<h2 align='center'>Bacteria 16S rRNA</h2> | |
| <h3 align='center'>BLAST 16S rRNA bacterial sequences and get a nice summary of the results with the power of AI!</h3> | |
| <h4 align='center'>Support this space with a ⭐ on <a href='https://github.com/AstraBert/BLAST-SummarAIzer'>GitHub</a></h4>""") | |
| demo1 = gr.ChatInterface(fn=ai_summarize, additional_inputs=[user_file1], additional_inputs_accordion=additional_accordion, title="""<h2 align='center'>Online BLAST results</h2> | |
| <h3 align='center'>Upload a Description Table from Online BLAST results and get a nice summary with the power of AI!</h3> | |
| <h4 align='center'>Support this space with a ⭐ on <a href='https://github.com/AstraBert/BLAST-SummarAIzer'>GitHub</a></h4>""") | |
| demo = gr.TabbedInterface([demo0, demo1], ["16S rRNA", "Online BLAST results"], title="BLAST SummarAIzer") | |
| if __name__=="__main__": | |
| demo.launch(server_name="0.0.0.0", share=False) |