Inicio

.gitignore

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+/venv/
+/__pycache__/
+bridges.py

Dockerfile

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+FROM python:3.13
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

LICENSE

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+MIT License
+
+Copyright (c) 2025 Moibe
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

app.py

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+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import StreamingResponse
+
+import io
+from io import BytesIO
+
+from fastapi import FastAPI, Form
+
+import funciones
+
+app = FastAPI()
+
+@app.post("/echo-image/")
+async def echo_image(image: UploadFile = File(...)):
+    if not image.content_type.startswith("image/"):
+        return {"error": "El archivo no es una imagen"}
+
+    contents = await image.read()
+    return StreamingResponse(BytesIO(contents), media_type=image.content_type)
+
+@app.post("/get-platillo/")
+async def get_platillo_image(prompt: str = Form(...)):
+    
+    imagen_pil = funciones.genera_platillo(prompt)
+
+    img_io = io.BytesIO()
+    imagen_pil.save(img_io, "PNG")
+    img_io.seek(0)
+    
+    #Ver cual es el mejor resultado para backend, si forzar la disposición de archivo o permitir que el navegador decida (puede que sea irrelevante para un consumo de la api directo)
+    #return StreamingResponse(content=img_io, media_type="image/png", headers={"Content-Disposition": "attachment; filename=platillo.png"})
+    return StreamingResponse(content=img_io, media_type="image/png")

enlaces.py

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+menu = [
+"Ensalada de atún con jitomate y queso",
+"Tuna and tomato salad with cheese",
+"Sopa de almeja con guisantes",
+"Pollo a la plancha con arroz y ensalada de lechuga", 
+"Tofu sobre rebanada de pan blanco"
+"Filete de carne con papas y ensalada verde"
+]
+
+espacios = [
+("stabilityai/stable-diffusion", "stabilityai/stable-diffusion"),
+("stabilityai/stable-diffusion-3-medium", "stabilityai/stable-diffusion-3-medium"),
+# ("stabilityai/stable-diffusion-3.5-large", "stabilityai/stable-diffusion-3.5-large"),
+("black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-schnell"),
+("black-forest-labs/FLUX.1-dev", "black-forest-labs/FLUX.1-dev")
+]
+
+modelos = [
+("stabilityai/stable-diffusion-xl-base-1.0", "stabilityai/stable-diffusion-xl-base-1.0"),
+("stabilityai/stable-diffusion-2", "stabilityai/stable-diffusion-2"),
+("stabilityai/stable-diffusion-2-1", "stabilityai/stable-diffusion-2-1"),
+("stabilityai/stable-diffusion-3-medium", "stabilityai/stable-diffusion-3-medium"),
+("stabilityai/stable-diffusion-3.5-large", "stabilityai/stable-diffusion-3.5-large"),
+("black-forest-labs/FLUX.1-dev", "black-forest-labs/FLUX.1-dev"),
+("black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-schnell")
+]
+
+proveedores_default = [
+("HF Inference", "hf-inference"),
+]
+
+proveedores_todos = [
+("HF Inference", "hf-inference"),
+("Together AI", "together"),
+("Fal AI", "fal-ai"),
+("Replicate", "replicate"),
+("Nebius", "nebius")
+]
+
+proveedores_sd1 = [
+("HF Inference", "hf-inference"),
+("Together AI", "together"),
+("Replicate", "replicate"),
+("Nebius", "nebius")
+]
+
+proveedores_sd2 = [
+("HF Inference", "hf-inference"),
+]
+
+proveedores_sd3_medium = [
+("Fal AI", "fal-ai"),
+]
+
+proveedores_sd3_large = [
+("HF Inference", "hf-inference"),
+("Fal AI", "fal-ai"),
+("Replicate", "replicate")
+]
+
+proveedores_flux = [
+("HF Inference", "hf-inference"),
+("Together AI", "together"),
+("Fal AI", "fal-ai"),
+("Replicate", "replicate"),
+("Nebius", "nebius")
+]

funciones.py

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+import bridges
+from huggingface_hub import InferenceClient
+from PIL import Image
+
+def genera_platillo(prompt): 
+    enlace = "black-forest-labs/FLUX.1-dev"
+    proveedor =  "hf-inference"
+
+    client = InferenceClient(
+            provider= proveedor,
+            api_key=bridges.hug
+        ) 
+    
+    #Testing change,
+
+    try: 
+        image = client.text_to_image(
+        prompt,
+        model=enlace,
+        #seed=42, #default varía pero el default es que siempre sea la misma.
+        #guidance_scale=7.5,
+        #num_inference_steps=50,
+        #width=1024, #El default es 1024 x 1024 y quizá 1024*768, el max es 1536. 
+        #height=1024 #El límite de replicate es 1024.
+        )
+
+        return image        
+        
+    except Exception as e:
+        print("Excepción es: ", e)

requirements.txt

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+fastapi
+fastapi[standard]
+
+huggingface_hub
+
+Pillow

tester.py

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+import funciones
+
+funciones.genera_platillo()