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README.md
25
README.md
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@ -1,12 +1,17 @@
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pip install llama-index
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pip install llama-index-llms-groq
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pip install llama-index-embeddings-huggingface
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pip install llama-parse
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pip install chromadb
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pip install llama-index-vector-stores-chroma
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pip install llama-index-embeddings-huggingface
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pip install python-fasthtml
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pip install grok
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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El sistema funciona en un docker
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para generar:
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docker build -t supertutor-app .
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para ejecutar:
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docker run -it -p 7884:7884 --rm fastapi-app
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si tienes problemas con permisos:
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sudo chmod 666 /var/run/docker.sock
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96
main.py
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main.py
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@ -12,7 +12,7 @@ from llama_index.core import Settings
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#from llama_index.embeddings.huggingface_api import (
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# HuggingFaceInferenceAPIEmbedding,
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#)
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import shutil
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import chromadb
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import os
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import threading
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@ -22,6 +22,9 @@ import json
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#from llama_index.llms.ollama import Ollama
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from llama_index.core.base.response.schema import Response
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from groq import Groq
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from fastapi import File as FileFast
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from fastapi import UploadFile as UploadFileFast
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from fastapi import Form as FormFast
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#import shutil
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pwd = os.getcwd()
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def extractConfig(nameModel="SystemData",relPath=os.path.join(pwd,"conf/experiment_config.json"),dataOut="keyantrophics"):
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@ -78,9 +81,9 @@ def checkInfoSources(user:str):
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subdir = [Option(file.name,value="static/"+user+"/"+file.name) for file in files if (file.is_dir() and file.name!="chroma_db") ]
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userdata=user
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print("Cambio",userdata)
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return Form(
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H3("Grupos de archivos",cls="col-xs-3"),
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H3("Grupo de archivos",cls="col-xs-3"),
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Select(
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*subdir,name="data",cls="col-xs-3"),
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Input(id="name-db", name="collection", placeholder="Enter a collection name",cls="col-xs-4"),
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@ -163,7 +166,7 @@ def loadCollection(data:str):
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def queryPrompt(question:str):
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#index=load_create_db(collection="my_collection")
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query_engine = index.as_query_engine(similarity_top_k=15,vector_store_query_mode="default",response_mode="tree_summarize")
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query_engine = index.as_query_engine(similarity_top_k=5,vector_store_query_mode="default",response_mode="tree_summarize")
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summary_prompt = (
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"Por favor, genera un resumen completo y detallado del material dado. "
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"Incluye los principales temas, argumentos y conclusiones. "
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@ -191,7 +194,7 @@ def queryPrompt(question:str):
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response2 = query_engine.query(tematic_prompt)
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response3 = query_engine.query(issues_prompt)
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response4 = query_engine.query(Question_prompt)
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Output="<H1>Summary</H1>"+str(response)+"<H1>Tematic</H1>"+str(response2)+"<H1>Issues</H1>"+str(response3)+"<H1>Questions</H1>"+str(response4)
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Output="<H1>Resumen</H1>"+str(response)+"<H1>Tematica</H1>"+str(response2)+"<H1>Problemas</H1>"+str(response3)+"<H1>Preguntas</H1>"+str(response4)
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return Output
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@ -239,10 +242,6 @@ Verificate if previous context is related to the previous response, if not, say
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The format of output is a json with keys 'coherencia', 'exactitud', 'relacion_con_el_contexto' and 'comentario' .
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'coherencia', 'exactitud', 'relacion_con_el_contexto' are numeric variables with max value is 10"""%(response,ContextNodes,message)
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print(chat_engine.__dict__)
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chat_completion = client.chat.completions.create(
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#
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# Required parameters
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@ -302,7 +301,7 @@ def SummarySources():
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return Form("Este es muy caro para documentos grandes y tarda mucho",
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Select(
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*subdir,name="data"),
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Input( name="query", placeholder="Enter a query"),
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Input( name="query", placeholder="Dar una pregunta"),
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Button("Submit",type="submit"), hx_post="/SummaryMake",hx_swap="innerHTML",hx_target="#summaryR" )
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@app.post("/SummaryMake")
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@ -374,18 +373,18 @@ def home():
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Div(Div(id="options",hx_target="this",hx_swap="outerHTML",hx_get="/listmodelactives",hx_trigger="click from:#buttonMenuuser delay:3s"),cls="col-xs-12"),
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Div(Div(id="Infomodel"),cls="col-xs-12"),
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#Div("Resumen",Div(id="summary",hx_target="this",hx_swap="outerHTML",hx_get="/SummarySources",hx_trigger="click from:#buttonMenuuser"),Div(id="summaryR")),
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Div(
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Div(H3("Chat para preguntarle al material de estudios "),
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Div(
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Form(
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Input(id="question", name="message", placeholder="Enter a message"),
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Input(id="question", name="message", placeholder="Dar una pregunta"),
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Button("Submit",type="submit"), hx_post="/chatData",hx_swap="afterend",hx_target="#questionR" ),
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Div(id="questionR")
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,id="questions"),
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cls="col-xs-6"),
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Div(
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Div(H3("Este genera informacion general del material, pero es intensivo en unso del api. No USAR."),
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Div(
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Form(
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Input(id="query", name="question", placeholder="Enter a query"),
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Input(id="query", name="question", placeholder="Dar una pregunta"),
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Button("Submit",type="submit"), hx_post="/queryprompt",hx_swap="innerHTML",hx_target="#queryR" ),
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Div(id="queryR"),
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id="query"),
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@ -394,14 +393,71 @@ def home():
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))
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return page
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# @app.post("/upload")
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# def upload(data: UploadFile = File(...),user : str = Form(...), dir: str = Form(...)):
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# filename="static/"+user+dir+data.filename
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@app.get("/fileup")
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def fileup():
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return Div(
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P('Upload data Super tutor'),
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Div(H2("Subir Archivos"),Form(
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Input(type='file', name='file',cls="col-xs-3"),
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Input( name='dir',placeholder="Enter a directory",cls="col-xs-2"),
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Input( name='user',placeholder="Enter a user",cls="col-xs-2"),
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Button('Upload', type='submit',cls="col-xs-4"),
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hx_post="/upload",
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hx_target="#info",
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hx_swap="innerHTML",
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enctype="multipart/form-data",
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),cls="col-xs-12"),
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Div(H2("Crear Usuario"),Form(
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Input( name='user',placeholder="Enter a user",cls="col-xs-7"),
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Button('Upload', type='submit',cls="col-xs-5"),
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hx_post="/createuser",
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hx_target="#info",
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hx_swap="innerHTML",
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enctype="multipart/form-data",
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),cls="col-xs-12"),
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Div(H2("Crear grupo de Archivos"),Form(
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Input( name='dir',placeholder="Enter a directory",cls="col-xs-4"),
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Input( name='user',placeholder="Enter a user",cls="col-xs-3"),
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Button('Upload', type='submit',cls="col-xs-5"),
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hx_post="/creategroup",
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hx_target="#info",
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hx_swap="innerHTML",
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enctype="multipart/form-data",
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),cls="col-xs-12"),
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Div(id="info")
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# with open(f"{filename}", "wb") as buffer:
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# shutil.copyfileobj(data.file, buffer)
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# app.mount("/static", StaticFiles(directory="static"), name="static")
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)
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@app.post("/upload")
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def upload(file: UploadFile,dir : str = Form(...),user : str = Form(...)):
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filenameB="static/"+user+"/"+dir+"/"+file.filename
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pathB="static/"+user+"/"+dir
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if not os.path.exists(pathB):
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os.makedirs(pathB)
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if not os.path.exists(filenameB):
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with open(f"{filenameB}", "wb") as buffer:
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shutil.copyfileobj(file.file, buffer)
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return P("Se ha subido %s"%(filenameB))
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@app.post("/createuser")
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def createuser(user : str = Form(...)):
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pathB="static/"+user
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if not os.path.exists(pathB):
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os.makedirs(pathB)
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return P("Se ha creado %s"%(pathB))
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@app.post("/creategroup")
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def createuser(user : str = Form(...),dir : str = Form(...)):
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pathB="static/"+user+"/"+dir
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if not os.path.exists(pathB):
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os.makedirs(pathB)
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return P("Se ha creado %s"%(pathB))
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app.mount("/static", StaticFiles(directory="static"), name="static")
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@ -0,0 +1,21 @@
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# Usar una imagen base de Python
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FROM python:3.11.10-bookworm
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# Establecer el directorio de trabajo en el contenedor
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WORKDIR /app
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# Copiar el archivo requirements.txt y otros archivos necesarios
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COPY requirements.txt ./
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# Instalar las dependencias de Python
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RUN pip install --no-cache-dir -r requirements.txt
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# Copiar todo el código de la aplicación al contenedor
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COPY . .
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# Expone el puerto que usará Uvicorn
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EXPOSE 7884
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# Especificar el comando
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7884", "--reload"]
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