Refactored things a bit
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.gitignore
vendored
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.gitignore
vendored
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@ -160,3 +160,4 @@ cython_debug/
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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.DS_Store
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@ -3,3 +3,8 @@ langchain-community
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openai
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fastapi
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pydantic-settings
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s3fs
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aiofiles
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duckdb
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polars
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pyarrow
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@ -5,6 +5,7 @@ class Settings(BaseSettings):
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anyscale_api_key: str = "Awesome API"
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gcs_access: str = "access"
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gcs_secret: str = "secret"
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gcs_bucketname: str = "bucket"
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model_config = SettingsConfigDict(env_file=".env")
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@ -1,15 +1,12 @@
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from pathlib import Path
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from fastapi import FastAPI, status
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from fastapi.responses import PlainTextResponse
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from fastapi.staticfiles import StaticFiles
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from langchain_community.chat_models import ChatAnyscale
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from langchain_core.messages import HumanMessage, SystemMessage
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from pydantic import BaseModel
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import hellocomputer
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from .config import settings
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from .routers import files, sessions
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static_path = Path(hellocomputer.__file__).parent / "static"
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@ -43,30 +40,8 @@ def get_health() -> HealthCheck:
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return HealthCheck(status="OK")
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@app.get("/greetings", response_class=PlainTextResponse)
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async def get_greeting() -> str:
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model = "meta-llama/Meta-Llama-3-8B-Instruct"
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chat = ChatAnyscale(
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model_name=model,
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temperature=0.5,
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anyscale_api_key=settings.anyscale_api_key,
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)
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messages = [
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SystemMessage(content="You are a helpful AI that shares everything you know."),
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HumanMessage(
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content="Make a short presentation of yourself "
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"as an assistant in Spanish in about 20 words. "
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"You're capable of analyzing a file that a user "
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"has previously uploaded."
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),
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]
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model_response = await chat.ainvoke(messages)
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print(model_response.response_metadata)
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return model_response.content
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app.include_router(sessions.router)
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app.include_router(files.router)
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app.mount(
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"/",
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StaticFiles(directory=static_path, html=True, packages=["bootstrap4"]),
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52
src/hellocomputer/models.py
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src/hellocomputer/models.py
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@ -0,0 +1,52 @@
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from enum import StrEnum
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from langchain_community.chat_models import ChatAnyscale
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from langchain_core.messages import HumanMessage, SystemMessage
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class AvailableModels(StrEnum):
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llama3_8b = "meta-llama/Meta-Llama-3-8B-Instruct"
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class Chat:
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@staticmethod
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def raise_no_key(api_key):
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if api_key:
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return api_key
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elif api_key is None:
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raise ValueError(
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"You need to provide a valid API in the api_key init argument"
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)
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else:
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raise ValueError("You need to provide a valid API key")
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def __init__(
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self,
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model: AvailableModels = AvailableModels.llama3_8b,
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api_key: str = "",
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temperature: float = 0.5,
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):
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self.model = model
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self.api_key = self.raise_no_key(api_key)
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self.messages = []
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self.responses = []
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model: ChatAnyscale = ChatAnyscale(
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model_name=model, temperature=temperature, anyscale_api_key=self.api_key
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)
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async def eval(self, system: str, human: str):
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self.messages.append(
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[
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SystemMessage(content=system),
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HumanMessage(content=human),
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]
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)
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self.responses.append(await self.model.ainvoke(self.messages[-1]))
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return self
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def last_response_content(self):
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return self.responses[-1].content
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def last_response_metadata(self):
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return self.responses[-1].response_metadata
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0
src/hellocomputer/routers/__init__.py
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0
src/hellocomputer/routers/__init__.py
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15
src/hellocomputer/routers/analysis.py
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15
src/hellocomputer/routers/analysis.py
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@ -0,0 +1,15 @@
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from fastapi import APIRouter
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from fastapi.responses import PlainTextResponse
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from ..config import settings
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from ..models import Chat
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router = APIRouter()
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@router.get("/query", response_class=PlainTextResponse, tags=["queries"])
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async def query(sid: str = "") -> str:
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model = Chat(api_key=settings.anyscale_api_key).eval(
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system="You're an expert analyst", human="Do some analysis"
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)
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return model.last_response_content()
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84
src/hellocomputer/routers/files.py
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84
src/hellocomputer/routers/files.py
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@ -0,0 +1,84 @@
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import aiofiles
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import duckdb
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import polars as pl
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import s3fs
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from fastapi import APIRouter, File, UploadFile
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from fastapi.responses import JSONResponse
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from ..config import settings
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router = APIRouter()
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# Configure the S3FS with your Google Cloud Storage credentials
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gcs = s3fs.S3FileSystem(
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key=settings.gcs_access,
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secret=settings.gcs_secret,
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client_kwargs={"endpoint_url": "https://storage.googleapis.com"},
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)
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bucket_name = settings.gcs_bucketname
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@router.post("/upload", tags=["files"])
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async def upload_file(file: UploadFile = File(...), sid: str = ""):
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async with aiofiles.tempfile.NamedTemporaryFile("wb") as f:
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content = await file.read()
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await f.write(content)
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await f.flush()
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gcs.makedir(f"{settings.gcs_bucketname}/{sid}")
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db = duckdb.connect()
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db.install_extension("spatial")
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db.install_extension("httpfs")
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db.load_extension("httpfs")
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db.load_extension("spatial")
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db.sql(f"""
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CREATE SECRET (
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TYPE GCS,
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KEY_ID '{settings.gcs_access}',
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SECRET '{settings.gcs_secret}')
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""")
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db.sql(f"""
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create table metadata as (
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select
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*
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from
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st_read('{f.name}',
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layer='metadata',
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open_options=['HEADERS_FORCE', 'FIELD_TYPES=auto']
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)
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)""")
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metadata = db.query("select * from metadata").pl()
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sheets = metadata.select(pl.col("Key") == "Sheets")
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print(sheets)
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for sheet in sheets.to_dict():
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print(sheet)
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db.sql(
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f"""
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create table data as (
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select
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*
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from
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st_read('{f.name}',
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layer='data',
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open_options=['HEADERS_FORCE', 'FIELD_TYPES=auto']
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)
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)"""
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)
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db.sql(f"""
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copy
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data
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to
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'gcs://{settings.gcs_bucketname}/{sid}/data.csv';
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""")
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return JSONResponse(
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content={"message": "File uploaded successfully"}, status_code=200
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)
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19
src/hellocomputer/routers/sessions.py
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src/hellocomputer/routers/sessions.py
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from uuid import uuid4
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from fastapi import APIRouter
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from fastapi.responses import PlainTextResponse
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router = APIRouter()
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@router.get("/new_session")
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async def get_new_session() -> str:
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return str(uuid4())
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@router.get("/greetings", response_class=PlainTextResponse)
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async def get_greeting() -> str:
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return (
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"Hi! I'm a helpful assistant. Please upload or select a file "
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"and I'll try to analyze it following your orders"
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)
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BIN
src/hellocomputer/static/.DS_Store
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BIN
src/hellocomputer/static/.DS_Store
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@ -51,6 +51,11 @@
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<div class="modal-body">
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<input type="file" class="custom-file-input" id="inputGroupFile01">
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</div>
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<div class="modal-body" id="uploadButtonDiv">
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<button type="button" class="btn btn-primary" id="uploadButton">Upload</button>
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</div>
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<div class="modal-body" id="uploadResultDiv">
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</div>
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<div class="modal-footer">
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<button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
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</div>
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@ -89,9 +94,6 @@
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<script src="https://cdn.jsdelivr.net/npm/bootstrap@5.2.3/dist/js/bootstrap.bundle.min.js"
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integrity="sha384-kenU1KFdBIe4zVF0s0G1M5b4hcpxyD9F7jL+jjXkk+Q2h455rYXK/7HAuoJl+0I4"
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crossorigin="anonymous"></script>
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<script src="https://unpkg.com/htmx.org@1.9.12"
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integrity="sha384-ujb1lZYygJmzgSwoxRggbCHcjc0rB2XoQrxeTUQyRjrOnlCoYta87iKBWq3EsdM2"
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crossorigin="anonymous"></script>
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<script src="script.js"></script>
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</body>
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@ -46,11 +46,18 @@ async function fetchResponse(message) {
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function addAIMessage() {
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const newMessage = document.createElement('div');
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newMessage.classList.add('message', 'bg-white', 'p-2', 'mb-2', 'rounded');
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newMessage.innerHTML = '<img src="/img/assistant.webp" width="50px"> <div id="spinner" class="spinner">';
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newMessage.innerHTML = '<img src="/img/assistant.webp" width="50px"> <div id="spinner" class="spinner"></div>';
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chatMessages.prepend(newMessage); // Add new message at the top
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fetchResponse(newMessage);
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}
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function addAIManualMessage(m) {
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const newMessage = document.createElement('div');
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newMessage.classList.add('message', 'bg-white', 'p-2', 'mb-2', 'rounded');
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newMessage.innerHTML = '<img src="/img/assistant.webp" width="50px"> <div>' + m + '</div>';
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chatMessages.prepend(newMessage); // Add new message at the top
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}
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function addUserMessage() {
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const messageContent = textarea.value.trim();
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if (messageContent) {
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@ -82,7 +89,11 @@ document.addEventListener("DOMContentLoaded", function () {
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async function fetchGreeting() {
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try {
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const response = await fetch('/greetings');
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const session_response = await fetch('/new_session');
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sessionStorage.setItem("helloComputerSession", JSON.parse(await session_response.text()));
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const response = await fetch('/greetings?sid=' + sessionStorage.getItem('helloComputerSession'));
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if (!response.ok) {
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throw new Error('Network response was not ok ' + response.statusText);
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}
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@ -101,3 +112,39 @@ document.addEventListener("DOMContentLoaded", function () {
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// Call the function to fetch greeting
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fetchGreeting();
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});
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document.addEventListener("DOMContentLoaded", function () {
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const fileInput = document.getElementById('inputGroupFile01');
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const uploadButton = document.getElementById('uploadButton');
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const uploadResultDiv = document.getElementById('uploadResultDiv');
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uploadButton.addEventListener('click', async function () {
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const file = fileInput.files[0];
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if (!file) {
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uploadResultDiv.textContent = 'Please select a file.';
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return;
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}
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const formData = new FormData();
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formData.append('file', file);
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try {
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const response = await fetch('/upload?sid=' + sessionStorage.getItem('helloComputerSession'), {
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method: 'POST',
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body: formData
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});
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if (!response.ok) {
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throw new Error('Network response was not ok ' + response.statusText);
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}
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const data = await response.text();
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uploadResultDiv.textContent = 'Upload successful: ' + JSON.parse(data)['message'];
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addAIManualMessage('File uploaded and processed!');
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} catch (error) {
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uploadResultDiv.textContent = 'Error: ' + error.message;
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}
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});
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});
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