updare

.gitignore

@@ -31,22 +31,21 @@ python/*/lib/
 .coverage
 coverage/
 licenses.txt
-notebooks/*/lancedb
-notebooks/*/data
+examples_notebooks/*/lancedb
+examples_notebooks/*/data
 tests/fixtures/cache
 tests/fixtures/*/cache
 tests/fixtures/*/output
 lancedb/
-graphfleet/cache
-graphfleet/output/20240828-113421
-graphfleet/output/20240828-113421/reports
+
 # Random
 .DS_Store
 *.log*
 .venv
+venv/
 .conda
 .tmp
-.genaiscript
+
 
 .env
 build.zip
@@ -56,7 +55,7 @@ build.zip
 __pycache__
 
 .pipeline
-.genaiscript
+
 # Azurite
 temp_azurite/
 __azurite*.json
@@ -68,28 +67,3 @@ ragtest/
 .ragtest/
 .pipelines
 .pipeline
-
-# Large files
-*.zip
-*.tar.gz
-*.7z
-*.rar
-*.iso
-*.dmg
-*.pkg
-*.exe
-*.deb
-*.rpm
-
-# Data and model files
-*.csv
-*.tsv
-*.json
-*.pkl
-*.h5
-*.pb
-
-# Directories
-data/
-models/
-logs/

README.md

@@ -148,7 +148,7 @@ Jupyter Notebooks: Explore GraphFleet's capabilities with the provided notebooks
 To run the API, save the code in a file named api.py and execute the following command in your terminal:
 
 ``` bash
-## uvicorn app:main --reload --port 8001 
+uvicorn app:main --reload --port 8001 
 ```
 
 ### Run the CLI commands to query the graph (Follow the get-started-graphfleet.ipynb notebook)

app/.streamlit/config.toml

@@ -0,0 +1,9 @@
+[theme]
+base="light"
+primaryColor="#2b2b2b"
+
+[server]
+port = 8501
+address = "0.0.0.0"
+
+[settings]

app/Dockerfile

@@ -0,0 +1,20 @@
+FROM python:3.11.5-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN git clone https://github.com/Qredence/GraphFleet.git .
+
+RUN pip3 install -r requirements.txt
+
+EXPOSE 8501
+
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
+ENTRYPOINT ["streamlit", "run", "streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

app/config.py

@@ -8,12 +8,16 @@
 
 class Settings(BaseSettings):
     API_KEY: str = os.getenv("GRAPHRAG_API_KEY", "default_api_key")
-    LLM_MODEL: str = os.getenv("GRAPHRAG_LLM_MODEL", "default_llm_model")
-    EMBEDDING_MODEL: str = os.getenv("GRAPHRAG_EMBEDDING_MODEL", "default_embedding_model")
+    LLM_MODEL: str = os.getenv("GRAPHRAG_LLM_MODEL", "gpt-4o-mini")
+    EMBEDDING_MODEL: str = os.getenv("GRAPHRAG_EMBEDDING_MODEL", "text-embedding-3-large")
     API_BASE: str = os.getenv("GRAPHRAG_API_BASE", "default_api_base")
     API_VERSION: str = os.getenv("GRAPHRAG_API_VERSION", "default_api_version")
-    INPUT_DIR: str = os.getenv("GRAPHRAG_INPUT_DIR", "graphfleet/output/20240829-184001/artifacts")
-    LANCEDB_URI: str = os.getenv("GRAPHRAG_LANCEDB_URI", "graphfleet/output/20240829-184001/artifacts/lancedb")
+    INPUT_DIR: str = os.getenv(
+        "GRAPHRAG_INPUT_DIR", "graphfleet/output/20240901-044131/artifacts"
+    )
+    LANCEDB_URI: str = os.getenv(
+        "GRAPHRAG_LANCEDB_URI", "graphfleet/output/20240901-044131/artifacts/lancedb"
+    )
     COMMUNITY_LEVEL: int = int(os.getenv("GRAPHRAG_COMMUNITY_LEVEL", 2))
     MAX_TOKENS: int = int(os.getenv("GRAPHRAG_MAX_TOKENS", 12000))
 

app/main.py

@@ -1,6 +1,7 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
+from pydantic_settings import BaseSettings, SettingsConfigDict  # Updated import
 from app.services.question_generator import create_question_generator
 from app.services.search_engine import create_search_engines, LocalSearchWrapper, GlobalSearchWrapper
 from app.routers import search
@@ -117,4 +118,6 @@ async def generate_questions(search_query: SearchQuery):
 
 @app.get("/")
 async def root():
-    return {"message": "Welcome to GraphFleet API"}
+    return {"message": "Welcome to GraphFleet API"}
+
+main = app