Compare commits
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c4b727ab19
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415e798021
| Author | SHA1 | Date |
|---|---|---|
 Mario Gil
|
415e798021 | |
|
Mario Gil
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f37e295ad9 |
25
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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|
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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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112
main.py
112
main.py
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@ -9,20 +9,23 @@ from llama_index.core import SummaryIndex
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from llama_index.llms.groq import Groq as GroqLLamaIndex
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from chromadb import PersistentClient
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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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#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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import time
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from llama_index.core.memory import ChatMemoryBuffer
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import json
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from llama_index.llms.ollama import Ollama
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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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import shutil
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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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configPath=os.path.join(os.getcwd(),relPath)
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@ -50,8 +53,8 @@ Settings.llm = llm_localLlamma
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gridlink = Link(rel="stylesheet", href="https://cdnjs.cloudflare.com/ajax/libs/flexboxgrid/6.3.1/flexboxgrid.min.css", type="text/css")
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app= FastHTML(hdrs=(picolink, gridlink))
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colorpico=Link(rel="stylesheet", href="https://cdn.jsdelivr.net/npm/@picocss/pico@2/css/pico.colors.min.css")
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app= FastHTML(hdrs=(picolink, gridlink,colorpico))
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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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@ -238,10 +241,6 @@ Evaluate the coherence and accuracy of previous response to respond %s in this e
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Verificate if previous context is related to the previous response, if not, say that you do not have information about that issue
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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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@ -293,7 +292,7 @@ The format of output is a json with keys 'coherencia', 'exactitud', 'relacion_co
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)
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return P(message),P(response),P(chat_completion.choices[0].message.content)
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return H6(message),P(response,cls="pico-color-pink-500"),P(chat_completion.choices[0].message.content,cls="pico-color-pink-500")
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@app.get("/SummarySources")
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def SummarySources():
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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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|
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|
|
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|
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@ -0,0 +1,146 @@
|
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aiohappyeyeballs==2.4.3
|
||||
aiohttp==3.10.9
|
||||
aiosignal==1.3.1
|
||||
annotated-types==0.7.0
|
||||
anyio==4.6.0
|
||||
asgiref==3.8.1
|
||||
attrs==24.2.0
|
||||
backoff==2.2.1
|
||||
bcrypt==4.2.0
|
||||
beautifulsoup4==4.12.3
|
||||
build==1.2.2.post1
|
||||
cachetools==5.5.0
|
||||
certifi==2024.8.30
|
||||
charset-normalizer==3.3.2
|
||||
chroma-hnswlib==0.7.6
|
||||
chromadb==0.5.7
|
||||
click==8.1.7
|
||||
coloredlogs==15.0.1
|
||||
dataclasses-json==0.6.7
|
||||
Deprecated==1.2.14
|
||||
dirtyjson==1.0.8
|
||||
distro==1.9.0
|
||||
durationpy==0.9
|
||||
fastapi==0.115.0
|
||||
fastcore==1.7.11
|
||||
fastlite==0.0.11
|
||||
filelock==3.16.1
|
||||
flatbuffers==24.3.25
|
||||
frozenlist==1.4.1
|
||||
fsspec==2024.9.0
|
||||
google-auth==2.35.0
|
||||
googleapis-common-protos==1.65.0
|
||||
greenlet==3.1.1
|
||||
groq==0.11.0
|
||||
grpcio==1.66.2
|
||||
h11==0.14.0
|
||||
httpcore==1.0.6
|
||||
httptools==0.6.1
|
||||
httpx==0.27.2
|
||||
huggingface-hub==0.25.1
|
||||
humanfriendly==10.0
|
||||
idna==3.10
|
||||
importlib_metadata==8.4.0
|
||||
importlib_resources==6.4.5
|
||||
itsdangerous==2.2.0
|
||||
jiter==0.6.1
|
||||
joblib==1.4.2
|
||||
kubernetes==31.0.0
|
||||
llama-cloud==0.1.2
|
||||
llama-index==0.11.13
|
||||
llama-index-agent-openai==0.3.4
|
||||
llama-index-cli==0.3.1
|
||||
llama-index-core==0.11.16
|
||||
llama-index-embeddings-huggingface==0.3.1
|
||||
llama-index-embeddings-openai==0.2.5
|
||||
llama-index-indices-managed-llama-cloud==0.4.0
|
||||
llama-index-legacy==0.9.48.post3
|
||||
llama-index-llms-openai==0.2.12
|
||||
llama-index-llms-groq==0.2.0
|
||||
llama-index-multi-modal-llms-openai==0.2.2
|
||||
llama-index-program-openai==0.2.0
|
||||
llama-index-question-gen-openai==0.2.0
|
||||
llama-index-readers-file==0.2.2
|
||||
llama-index-readers-llama-parse==0.3.0
|
||||
llama-index-vector-stores-chroma==0.2.0
|
||||
llama-parse==0.5.7
|
||||
markdown-it-py==3.0.0
|
||||
marshmallow==3.22.0
|
||||
mdurl==0.1.2
|
||||
mmh3==5.0.1
|
||||
monotonic==1.6
|
||||
mpmath==1.3.0
|
||||
multidict==6.1.0
|
||||
mypy-extensions==1.0.0
|
||||
nest-asyncio==1.6.0
|
||||
networkx==3.3
|
||||
nltk==3.9.1
|
||||
numpy==1.26.4
|
||||
oauthlib==3.2.2
|
||||
onnxruntime==1.19.2
|
||||
openai==1.51.1
|
||||
opentelemetry-api==1.27.0
|
||||
opentelemetry-exporter-otlp-proto-common==1.27.0
|
||||
opentelemetry-exporter-otlp-proto-grpc==1.27.0
|
||||
opentelemetry-instrumentation==0.48b0
|
||||
opentelemetry-instrumentation-asgi==0.48b0
|
||||
opentelemetry-instrumentation-fastapi==0.48b0
|
||||
opentelemetry-proto==1.27.0
|
||||
opentelemetry-sdk==1.27.0
|
||||
opentelemetry-semantic-conventions==0.48b0
|
||||
opentelemetry-util-http==0.48b0
|
||||
orjson==3.10.7
|
||||
overrides==7.7.0
|
||||
packaging==24.1
|
||||
pandas==2.2.3
|
||||
pillow==10.4.0
|
||||
posthog==3.7.0
|
||||
propcache==0.2.0
|
||||
protobuf==4.25.5
|
||||
pyasn1==0.6.1
|
||||
pyasn1_modules==0.4.1
|
||||
pydantic==2.9.2
|
||||
pydantic_core==2.23.4
|
||||
Pygments==2.18.0
|
||||
pypdf==4.3.1
|
||||
PyPika==0.48.9
|
||||
pyproject_hooks==1.2.0
|
||||
pysqlite3-binary==0.5.3.post1
|
||||
pysqlite3-binary==0.5.3.post1
|
||||
python-dateutil==2.9.0.post0
|
||||
python-dotenv==1.0.1
|
||||
python-fasthtml==0.6.7
|
||||
python-multipart==0.0.12
|
||||
pytz==2024.2
|
||||
PyYAML==6.0.2
|
||||
regex==2024.9.11
|
||||
requests==2.32.3
|
||||
requests-oauthlib==2.0.0
|
||||
rich==13.9.2
|
||||
rsa==4.9
|
||||
shellingham==1.5.4
|
||||
six==1.16.0
|
||||
sniffio==1.3.1
|
||||
soupsieve==2.6
|
||||
SQLAlchemy==2.0.35
|
||||
sqlite-minutils==3.37.0.post3
|
||||
starlette==0.38.6
|
||||
striprtf==0.0.26
|
||||
sympy==1.13.3
|
||||
tenacity==8.5.0
|
||||
tiktoken==0.8.0
|
||||
tokenizers==0.20.0
|
||||
tqdm==4.66.5
|
||||
typer==0.12.5
|
||||
typing-inspect==0.9.0
|
||||
typing_extensions==4.12.2
|
||||
tzdata==2024.2
|
||||
urllib3==2.2.3
|
||||
uvicorn==0.31.0
|
||||
uvloop==0.20.0
|
||||
watchfiles==0.24.0
|
||||
websocket-client==1.8.0
|
||||
websockets==13.1
|
||||
wrapt==1.16.0
|
||||
yarl==1.14.0
|
||||
zipp==3.20.2
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
# Usar una imagen base de Python
|
||||
FROM python:3.11.10-bookworm
|
||||
# Establecer el directorio de trabajo en el contenedor
|
||||
WORKDIR /app
|
||||
|
||||
# Copiar el archivo requirements.txt y otros archivos necesarios
|
||||
COPY requirements.txt ./
|
||||
|
||||
# Instalar las dependencias de Python
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
|
||||
# Copiar todo el código de la aplicación al contenedor
|
||||
COPY . .
|
||||
|
||||
# Expone el puerto que usará Uvicorn
|
||||
EXPOSE 7884
|
||||
|
||||
# Especificar el comando
|
||||
|
||||
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7884", "--reload"]
|
||||
|
||||
Loading…
Reference in New Issue