README.md

@@ -1,17 +1,12 @@
-El sistema funciona en un docker 
+pip install llama-index
-para generar:
+pip install llama-index-llms-groq
-
+pip install llama-index-embeddings-huggingface
-docker build -t supertutor-app .
+pip install llama-parse
+pip install chromadb
+pip install llama-index-vector-stores-chroma
+pip install llama-index-embeddings-huggingface
+pip install python-fasthtml
+pip install grok
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
 
 
-
-para ejecutar:
-
-docker run -it -p 7884:7884 --rm fastapi-app
-
-
-
-si tienes problemas con permisos:
-
-sudo chmod 666 /var/run/docker.sock
-

dockerfile

@@ -1,21 +0,0 @@
-# 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"]
-

main.py

@@ -9,23 +9,20 @@ from llama_index.core import SummaryIndex
 from llama_index.llms.groq import Groq as GroqLLamaIndex
 from chromadb import PersistentClient
 from llama_index.core import Settings
-#from llama_index.embeddings.huggingface_api import (
+from llama_index.embeddings.huggingface_api import (
-#    HuggingFaceInferenceAPIEmbedding,
+    HuggingFaceInferenceAPIEmbedding,
-#)
+)
-import shutil
+
 import chromadb
 import os
 import threading
 import time
 from llama_index.core.memory import ChatMemoryBuffer
 import json
-#from llama_index.llms.ollama import Ollama
+from llama_index.llms.ollama import Ollama
 from llama_index.core.base.response.schema import Response
 from groq import Groq
-from fastapi import  File as FileFast
+import shutil
-from fastapi import UploadFile as UploadFileFast
-from fastapi import Form as FormFast
-#import shutil
 pwd = os.getcwd()
 def extractConfig(nameModel="SystemData",relPath=os.path.join(pwd,"conf/experiment_config.json"),dataOut="keyantrophics"):
     configPath=os.path.join(os.getcwd(),relPath)
@@ -53,8 +50,8 @@ Settings.llm = llm_localLlamma
 
 
 gridlink = Link(rel="stylesheet", href="https://cdnjs.cloudflare.com/ajax/libs/flexboxgrid/6.3.1/flexboxgrid.min.css", type="text/css")
-colorpico=Link(rel="stylesheet", href="https://cdn.jsdelivr.net/npm/@picocss/pico@2/css/pico.colors.min.css")
+
-app= FastHTML(hdrs=(picolink, gridlink,colorpico))
+app= FastHTML(hdrs=(picolink, gridlink))
 
 
 
@@ -81,9 +78,9 @@ def checkInfoSources(user:str):
         subdir = [Option(file.name,value="static/"+user+"/"+file.name) for file in files if  (file.is_dir() and file.name!="chroma_db") ]
     
     userdata=user
-
+    print("Cambio",userdata)
     return Form(
-    H3("Grupo de archivos",cls="col-xs-3"),
+    H3("Grupos de archivos",cls="col-xs-3"),
     Select(
     *subdir,name="data",cls="col-xs-3"),
     Input(id="name-db", name="collection", placeholder="Enter a collection name",cls="col-xs-4"),
@@ -166,7 +163,7 @@ def loadCollection(data:str):
 def queryPrompt(question:str):
     #index=load_create_db(collection="my_collection")
     
-    query_engine = index.as_query_engine(similarity_top_k=5,vector_store_query_mode="default",response_mode="tree_summarize")
+    query_engine = index.as_query_engine(similarity_top_k=15,vector_store_query_mode="default",response_mode="tree_summarize")
     summary_prompt = (
         "Por favor, genera un resumen completo y detallado del material dado. "
         "Incluye los principales temas, argumentos y conclusiones. "
@@ -194,7 +191,7 @@ def queryPrompt(question:str):
     response2 = query_engine.query(tematic_prompt)
     response3 = query_engine.query(issues_prompt)
     response4 = query_engine.query(Question_prompt)
-    Output="<H1>Resumen</H1>"+str(response)+"<H1>Tematica</H1>"+str(response2)+"<H1>Problemas</H1>"+str(response3)+"<H1>Preguntas</H1>"+str(response4)
+    Output="<H1>Summary</H1>"+str(response)+"<H1>Tematic</H1>"+str(response2)+"<H1>Issues</H1>"+str(response3)+"<H1>Questions</H1>"+str(response4)
 
     return Output
 
@@ -241,6 +238,10 @@ Evaluate the coherence and accuracy of previous response to respond %s in this e
 Verificate if previous context is related to the previous response, if not, say that you do not have information about that issue 
 The format of output is a json with keys 'coherencia', 'exactitud', 'relacion_con_el_contexto' and 'comentario' .
 'coherencia', 'exactitud', 'relacion_con_el_contexto' are numeric variables with max value is 10"""%(response,ContextNodes,message)
+        
+
+
+    print(chat_engine.__dict__)
 
     chat_completion = client.chat.completions.create(
     #
@@ -292,7 +293,7 @@ The format of output is a json with keys 'coherencia', 'exactitud', 'relacion_co
     )
 
 
-    return H6(message),P(response,cls="pico-color-pink-500"),P(chat_completion.choices[0].message.content,cls="pico-color-pink-500")
+    return P(message),P(response),P(chat_completion.choices[0].message.content)
 
 @app.get("/SummarySources")
 def SummarySources():
@@ -301,7 +302,7 @@ def SummarySources():
     return Form("Este es muy caro para documentos grandes y tarda mucho",
     Select(
     *subdir,name="data"),
-    Input( name="query", placeholder="Dar una pregunta"),
+    Input( name="query", placeholder="Enter a query"),
         Button("Submit",type="submit"), hx_post="/SummaryMake",hx_swap="innerHTML",hx_target="#summaryR" )
 
 @app.post("/SummaryMake")
@@ -373,18 +374,18 @@ def home():
                     Div(Div(id="options",hx_target="this",hx_swap="outerHTML",hx_get="/listmodelactives",hx_trigger="click from:#buttonMenuuser delay:3s"),cls="col-xs-12"),
                     Div(Div(id="Infomodel"),cls="col-xs-12"),
                     #Div("Resumen",Div(id="summary",hx_target="this",hx_swap="outerHTML",hx_get="/SummarySources",hx_trigger="click from:#buttonMenuuser"),Div(id="summaryR")),
-                    Div(H3("Chat para preguntarle al material de estudios "),
+                    Div(
                         Div(
                             Form(
-                                Input(id="question", name="message", placeholder="Dar una pregunta"),
+                                Input(id="question", name="message", placeholder="Enter a message"),
                                 Button("Submit",type="submit"), hx_post="/chatData",hx_swap="afterend",hx_target="#questionR" ),
                             Div(id="questionR")
                         ,id="questions"),
                     cls="col-xs-6"),
-                    Div(H3("Este genera informacion general del material, pero es intensivo en unso del api. No USAR."),
+                    Div(
                         Div(
                             Form(
-                                Input(id="query", name="question", placeholder="Dar una pregunta"),
+                                Input(id="query", name="question", placeholder="Enter a query"),
                                 Button("Submit",type="submit"), hx_post="/queryprompt",hx_swap="innerHTML",hx_target="#queryR" ),
                             Div(id="queryR"),
                             id="query"),
@@ -393,71 +394,14 @@ def home():
                 ))
     return page
 
-@app.get("/fileup")
+# @app.post("/upload")
-def fileup():
+# def upload(data: UploadFile = File(...),user : str = Form(...), dir: str = Form(...)):
-    return Div(
+#     filename="static/"+user+dir+data.filename
-        P('Upload data Super tutor'),
-        Div(H2("Subir Archivos"),Form(
-            Input(type='file', name='file',cls="col-xs-3"),
-            Input( name='dir',placeholder="Enter a directory",cls="col-xs-2"),
-            Input( name='user',placeholder="Enter a user",cls="col-xs-2"),
-            Button('Upload', type='submit',cls="col-xs-4"),
-            hx_post="/upload",
-            hx_target="#info",
-            hx_swap="innerHTML",
-            enctype="multipart/form-data",
-        ),cls="col-xs-12"),
-        Div(H2("Crear Usuario"),Form(
-            Input( name='user',placeholder="Enter a user",cls="col-xs-7"),
-            Button('Upload', type='submit',cls="col-xs-5"),
-            hx_post="/createuser",
-            hx_target="#info",
-            hx_swap="innerHTML",
-            enctype="multipart/form-data",
-        ),cls="col-xs-12"),
-        Div(H2("Crear grupo de Archivos"),Form(
-            Input( name='dir',placeholder="Enter a directory",cls="col-xs-4"),
-            Input( name='user',placeholder="Enter a user",cls="col-xs-3"),
-            Button('Upload', type='submit',cls="col-xs-5"),
-            hx_post="/creategroup",
-            hx_target="#info",
-            hx_swap="innerHTML",
-            enctype="multipart/form-data",
-        ),cls="col-xs-12"),
-        Div(id="info")
 
+#     with open(f"{filename}", "wb") as buffer:
+#         shutil.copyfileobj(data.file, buffer)
 
-    )
+# app.mount("/static", StaticFiles(directory="static"), name="static")
-    
-
-@app.post("/upload")
-def upload(file: UploadFile,dir : str = Form(...),user : str = Form(...)):
-    filenameB="static/"+user+"/"+dir+"/"+file.filename
-    pathB="static/"+user+"/"+dir
-    if not os.path.exists(pathB):
-        os.makedirs(pathB)
-    if not os.path.exists(filenameB):
-        with open(f"{filenameB}", "wb") as buffer:
-            shutil.copyfileobj(file.file, buffer)
-    return P("Se ha subido %s"%(filenameB))
-    
-
-@app.post("/createuser")
-def createuser(user : str = Form(...)):
-    pathB="static/"+user
-    if not os.path.exists(pathB):
-        os.makedirs(pathB)
-    return P("Se ha creado %s"%(pathB))
-
-@app.post("/creategroup")
-def createuser(user : str = Form(...),dir : str = Form(...)):
-    pathB="static/"+user+"/"+dir
-    if not os.path.exists(pathB):
-        os.makedirs(pathB)
-    return P("Se ha creado %s"%(pathB))
-
-
-app.mount("/static", StaticFiles(directory="static"), name="static")
 
 
 

requirements.txt

@@ -1,146 +0,0 @@
-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

run.sh

@@ -1 +0,0 @@
-docker run -it -p 7884:7884 --rm fastapi-app

static/Ricardo/PCL/dockerfile

@@ -1,21 +0,0 @@
-# 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"]
-