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| import gradio as gr | |
| import torch | |
| import os | |
| import torchvision | |
| from transformers import pipeline | |
| auth_token = os.environ.get("HUGGING_FACE_HUB_TOKEN") | |
| # Function to generate output based on input | |
| def generate_output(input_text, max_new_tokens, temperature, top_k, top_p, model): | |
| # Initialize the pipeline | |
| pipe = pipeline( | |
| "text-generation", | |
| model=model, | |
| torch_dtype=torch.bfloat16, | |
| device_map="auto" | |
| ) | |
| # Prompt for extracting information | |
| prompt = f''' | |
| Your task is to extract the information corresponding to the provided labels from the below given email. | |
| ### Labels: | |
| * pickup_location: Street address of the origin location of goods. | |
| * pickup_cap: Postal code or ZIP code of the pickup location. | |
| * pickup_port: Port of pickup, often used in international shipping. | |
| * pickup_state: Only Country of pickup location. | |
| * delivery_location: Street address of the destination location of goods. | |
| * delivery_cap: Postal code or ZIP code of delivery location. | |
| * delivery_port: Port of delivery, similar to pickup port. | |
| * delivery_state: State or region of delivery location. | |
| * total_quantity: Overall quantity of shipped items (e.g., pieces, boxes). Calculate the total_quantity by summing the quantity of all packages. | |
| * total_weight: Total weight of the shipment (e.g., kg, lbs). Calculate the total_weight by summing the weights of all packages. | |
| * total_volume: Total volume of the shipment (e.g., cubic meters, cubic feet). Calculate the total_volume by summing the volumes of all packages. | |
| * quantity: Individual Quantity of a specific item being shipped. | |
| * package_type: Individual Type of packaging used (e.g., pallets, cartons). | |
| * weight: Individual Weight of a specific package. | |
| * measures: Individual Dimensions or measurements of a package. | |
| * stackable: Indicates whether the shipment is stackable (True or False). | |
| * volume: Individual Volume of a specific package. | |
| * commodity: Type of goods or commodities being shipped. | |
| * company: Name of the email sending company, also the shipping company or carrier. | |
| * incoterms: Choose available options: EXW, FCA, FAS, FOB, CFR, CIF, CPT, CIP, DAP, DPU, DDP. | |
| For attributes with multiple values, such as measures, volume, weight, package_type, and quantity, provide each value separately in a JSON format. | |
| ### Input data: | |
| {input_text} | |
| ### Output: | |
| ''' | |
| # Generate the result | |
| result = pipe( | |
| f"<s>[INST] {prompt} [/INST]", | |
| do_sample=True, | |
| max_new_tokens=max_new_tokens, | |
| temperature=temperature, | |
| top_k=top_k, | |
| top_p=top_p, | |
| num_return_sequences=1, | |
| ) | |
| # Return the generated text | |
| return result[0]['generated_text'] | |
| examples = [ | |
| ''' | |
| COTIZACION FLETE MARITIMO OC 4500325343 Buongiorno ; | |
| Se mi potete quotare: ; | |
| NOT STACKABLE ; | |
| Delivery terms : FCA Anzano del Parco (Como) Italy ; | |
| Pick up address : ; SOREMA Div. of PREVIERO N.S.R.L. ; Via per Cavolto 17 - 22040 Anzano del Parco-CO, Italy ; | |
| Warehouse opening : From 8.30 to 12 h. // from 13,30 to 16,30 h. ; | |
| PO NO. ; DESCRIPTION ; SIZES cm ; WEIGHT ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 30 h ; Kg 315 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 40 h ; Kg 350 ; | |
| 4500325343 ; No. 1 CASE ; 85 x 75 x 40 h ; Kg 350 ; | |
| DESTINO: Veracruz, Mexico ; Gracias y saludos ; | |
| Ivan Briana ; Sales and Operations Manager ; | |
| Tel: +52 55 7155 6559/7098 6337 ; Mobile: +52 (55) 6963 2573 ; | |
| CERMESONI MEXICO S.A.DE C.V. ; Blvd. Adolfo Lopez Mateos no. 202 ; | |
| Col. San Pedro de los Pinos ; | |
| Del. Alvaro Obregon ; | |
| 01180 Ciudad de Mexico ;'''] | |
| # Create Gradio inputs | |
| inputs = [ | |
| gr.inputs.Textbox(label="Input Text"), | |
| gr.inputs.Number(label="Max New Tokens", default=32000), | |
| gr.inputs.Slider(label="Temperature", minimum=0.0, maximum=1.0, default=0.1, step=0.01), | |
| gr.inputs.Number(label="Top K", default=0), | |
| gr.inputs.Number(label="Top P", default=0), | |
| gr.inputs.Textbox(label="Model", default="Jyotiyadav/mistral_7B_NER") | |
| ] | |
| # Create a Gradio interface | |
| iface = gr.Interface( | |
| fn=generate_output, | |
| inputs=inputs, | |
| outputs="text", | |
| #examples=examples, | |
| title="Information Extraction with Mistral-7B", | |
| description="Generate Information Extraction with OpenLLM.", | |
| debug=True | |
| ) | |
| # Launch the interface | |
| iface.launch() |