Create app.py

app.py

@@ -0,0 +1,87 @@
+import gradio as gr
+import json
+from huggingface_hub import InferenceClient
+
+client = InferenceClient(
+    "mistralai/Mistral-7B-Instruct-v0.1"
+)
+
+rag_text = "Este es el texto RAG"
+prompt_template_text = "Este es el texto del template de prompt"
+
+def format_prompt(message):
+  prompt = "<s>"
+  prompt += f"[INST] {message} [/INST]"
+  return prompt
+
+def generate(prompt):
+
+    generate_kwargs = dict(
+        temperature=0.9,
+        max_new_tokens=1024,
+        top_p=0.95,
+        repetition_penalty=1.0,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+
+def process_input(text, rag, prompt_template):
+    prompt = text
+    if rag:
+        prompt += rag_text
+    if prompt_template:
+        prompt += prompt_template_text
+    json_text = generate(prompt)
+    
+    # Convertimos el generador en una cadena JSON
+    json_str = ''.join(json_text)
+
+    # Convertimos la cadena JSON en un objeto JSON
+    json_obj = json.loads(json_str)
+
+    # Generamos el archivo JSON
+    with open('output.json', 'w') as f:
+        json.dump(json_obj, f)
+    
+    return text
+
+def create_interface():
+    # Definimos los componentes de la interfaz
+    input_text = gr.Textbox(label="Input")
+    rag_checkbox = gr.Checkbox(label="RAG")
+    prompt_template = gr.Checkbox(label="PromptTemplate")
+    output_text = gr.Textbox(label="Output")
+    classification_types_checkboxes = gr.CheckboxGroup(label="Clasificacion Tipo")
+
+    # Definimos la función que se ejecutará cuando se envíe la entrada
+    def fn(text, rag, prompt_template):
+        output = process_input(text, rag, prompt_template)
+        with open('output.json', 'r') as f:
+            data = json.load(f)
+        classification_types = [item['clasificacion_tipo'] for item in data]
+        classification_types_options = [(option, option) for option in classification_types]
+        classification_types_checkboxes = gr.CheckboxGroup(label="Clasificacion Tipo", choices=classification_types_options, interactive = True)
+        return output, classification_types_checkboxes
+
+    # Creamos la interfaz
+    iface = gr.Interface(
+        fn=fn,
+        inputs=[input_text, rag_checkbox, prompt_template],
+        outputs=[output_text, classification_types_checkboxes]
+    )
+
+    return iface
+
+iface = create_interface()
+iface.launch()