Upload folder using huggingface_hub

.gitignore

@@ -0,0 +1,162 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+.DS_Store
+db/
+backend/static
+backend/media
+backend/db.sqlite3
+
+.terraform
+
+db/

README.md

@@ -1,12 +1,72 @@
----
-title: Rag Full
-emoji: 🚀
-colorFrom: pink
-colorTo: green
-sdk: gradio
-sdk_version: 4.43.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Embedchain Admin
+
+Welcome to the Embedchain Admin repository. This toolkit helps you build a full-stack RAG (Retrieve, Append, Generate) application with a focus on simplicity and functionality, powered by Embedchain.
+
+## 🚀 Features
+
+- **Chat Interface:** A clean and simple interface for messaging.
+- **Streaming:** Supports live data streaming.
+- **Citations:** Allows integration of citations within the chat.
+- **Model Support:** Compatible with both proprietary and open-source models.
+- **Admin Panel:**
+    - View chat history.
+    - Manage embeddings.
+    - Configure data sources through the UI.
+
+## Tech Stack
+
+This project uses:
+
+- FastAPI: For the backend, making it fast and easy to develop.
+- NextJS: For the frontend, enabling responsive and dynamic web pages.
+- Embedchain: Powers the core functionalities like chat and streaming.
+
+
+## Getting Started
+
+To start using Embedchain Admin for your project, install python package using:
+
+```bash
+pip install embedchain
+```
+
+Now, if you use docker, you can simply run the following commands:
+
+### With docker
+```bash
+ec create-app my-app --docker
+cd my-app
+ec start --docker
+```
+
+### Without docker
+
+```bash
+ec create-app my-app
+cd my-app
+ec start
+```
+
+You are all set now. Open http://localhost:3000 to view the chat UI.
+
+## Screenshots
+
+### Chat
+
+<img src="assets/chat.png" height="600px" />
+
+### Search
+
+<img src="assets/search.png" height="600px" />
+
+### Chat history
+
+<img src="assets/chat_history.png" height="600px" />
+
+### Collections
+
+<img src="assets/collection.png" height="600px" />
+
+### Data sources
+
+<img src="assets/add_data.png" height="600px" />

api/Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt /app/
+
+RUN pip install -r requirements.txt
+
+COPY . /app
+
+EXPOSE 8000
+
+CMD ["python", "-m", "main"]

api/main.py

@@ -0,0 +1,19 @@
+import uvicorn
+from dotenv import load_dotenv
+from fastapi import FastAPI
+
+from routes import api
+from routes.admin import chat_history, data_sources, vector_stores
+
+load_dotenv(".env")
+
+app = FastAPI(title="Embedchain API")
+
+app.include_router(api.router)
+app.include_router(data_sources.router)
+app.include_router(chat_history.router)
+app.include_router(vector_stores.router)
+
+if __name__ == "__main__":
+    uvicorn.run("main:app", host="0.0.0.0", port=8000, log_level="info",
+                reload=True, timeout_keep_alive=600)

api/requirements.txt

@@ -0,0 +1,7 @@
+fastapi==0.108.0
+uvicorn==0.25.0
+embedchain
+beautifulsoup4
+sentence-transformers
+langchain_huggingface
+langchain_community

api/routes/admin/chat_history.py

@@ -0,0 +1,19 @@
+from embedchain import App
+from fastapi import APIRouter
+
+from utils.embedchain import EC_APP_CONFIG
+
+ec_app = App.from_config(config=EC_APP_CONFIG)
+
+router = APIRouter()
+
+
+@router.get("/api/v1/admin/chat_history")
+async def get_all_chat_history():
+    chat_history = ec_app.llm.memory.get(
+        app_id=ec_app.config.id,
+        num_rounds=100,
+        display_format=True,
+        fetch_all=True,
+    )
+    return chat_history

api/routes/admin/data_sources.py

@@ -0,0 +1,57 @@
+from embedchain import App
+from fastapi import APIRouter, Response, status
+from pydantic import BaseModel
+
+from routes.admin.utils import (set_env_variables, unset_env_variables,
+                                validate_json)
+from utils.embedchain import EC_APP_CONFIG
+
+router = APIRouter()
+ec_app = App.from_config(config=EC_APP_CONFIG)
+
+
+class DataSourceModel(BaseModel):
+    dataType: str
+    dataValue: str
+    metadata: str
+    envVariables: str
+
+
+@router.get("/api/v1/admin/data_sources")
+async def get_all_data_sources():
+    data_sources = ec_app.get_data_sources()
+    response = data_sources
+    for i in response:
+        i.update({"app_id": ec_app.config.id})
+    return response
+
+
+@router.post("/api/v1/admin/data_sources", status_code=201)
+async def add_data_source(data_source: DataSourceModel, response: Response):
+    """
+    Adds a new source to the Embedchain app.
+    """
+    data_type = data_source.dataType
+    data_value = data_source.dataValue
+    metadata = data_source.metadata
+    env_variables = data_source.envVariables
+
+    # Validate json metadata
+    params = {"source": data_value, "data_type": data_type}
+    if metadata and not validate_json(metadata):
+        response.status_code = status.HTTP_400_BAD_REQUEST
+        return {"message": "Invalid metadata. Enter a valid JSON object."}
+
+    if env_variables and not validate_json(env_variables):
+        response.status_code = status.HTTP_400_BAD_REQUEST
+        return {"message": "Invalid environment variables. Enter a valid JSON object."}
+
+    try:
+        set_env_variables(env_variables)
+        ec_app.add(**params)
+        unset_env_variables(env_variables)
+        return {"message": f"Data of {data_type=} added successfully."}
+    except Exception as e:
+        message = f"An error occurred: Error message: {str(e)}."  # noqa:E501
+        response.status_code = status.HTTP_400_BAD_REQUEST
+        return {"message": message}

api/routes/admin/embeddings.py

@@ -0,0 +1,39 @@
+import chromadb
+from chromadb.config import Settings
+from fastapi import APIRouter
+
+router = APIRouter()
+
+
+chroma_settings = Settings(
+    anonymized_telemetry=False,
+    persist_directory="db",
+    allow_reset=False,
+    is_persistent=True,
+)
+client = chromadb.Client(chroma_settings)
+
+
+@router.get("/api/v1/admin/collections")
+async def get_all_collections():
+    # Currently only works for ChromaDB but can be extended easily
+    # for other vector stores as well
+    collections = client.list_collections()
+    responses = [c.dict() for c in collections]
+    return responses
+
+
+# TODO(deshraj): Add pagination and make this endpoint agnostic to the vector store
+@router.get("/api/v1/admin/collections/chromadb/{collection_name}")
+async def get_collection_details(collection_name: str):
+    collection = client.get_collection(collection_name)
+    collection_data = collection.get()
+    metadatas, documents = collection_data['metadatas'], collection_data['documents']
+    collated_data = []
+    for i in zip(metadatas, documents):
+        collated_data.append({
+            "metadata": i[0],
+            "document": i[1]
+        })
+    response = {"details": collection.model_dump(), "data": collated_data}
+    return response

api/routes/admin/utils.py

@@ -0,0 +1,30 @@
+import json
+import os
+
+
+def set_env_variables(env_variables: str):
+    if env_variables:
+        try:
+            env_variables = json.loads(env_variables)
+            for k, v in env_variables.items():
+                os.environ[k] = v
+        except Exception:
+            raise Exception("Invalid envVariables: Enter a valid JSON object.")
+
+
+def unset_env_variables(env_variables: str):
+    if env_variables:
+        try:
+            env_variables = json.loads(env_variables)
+            for k, v in env_variables.items():
+                os.environ.pop(k)
+        except Exception:
+            raise Exception("Invalid envVariables: Enter a valid JSON object.")
+
+
+def validate_json(json_string: str):
+    try:
+        json.loads(json_string)
+        return True
+    except Exception:
+        return False

api/routes/admin/vector_stores.py

@@ -0,0 +1,31 @@
+from embedchain import App
+from fastapi import APIRouter
+
+from utils.embedchain import EC_APP_CONFIG
+
+router = APIRouter()
+ec_app = App.from_config(config=EC_APP_CONFIG)
+
+
+@router.get("/api/v1/admin/collections")
+async def get_all_collections():
+    # Currently only works for ChromaDB but can be extended easily
+    # for other vector stores as well
+    collections = ec_app.db.client.list_collections()
+    responses = [c.dict() for c in collections]
+    return responses
+
+
+@router.get("/api/v1/admin/collections/chromadb/{collection_name}")
+async def get_collection_details(collection_name: str):
+    collection = ec_app.db.client.get_collection(collection_name)
+    collection_data = collection.get()
+    metadatas, documents = collection_data['metadatas'], collection_data['documents']
+    collated_data = []
+    for i in zip(metadatas, documents):
+        collated_data.append({
+            "metadata": i[0],
+            "document": i[1]
+        })
+    response = {"details": collection.dict(), "data": collated_data}
+    return response

api/routes/api.py

@@ -0,0 +1,21 @@
+from fastapi import APIRouter, Query, responses
+from fastapi.responses import StreamingResponse
+
+from utils.embedchain import send_message
+
+router = APIRouter()
+
+
+@router.get("/api/v1/chat")
+async def handle_chat(query: str, session_id: str = Query(None), number_documents: int = 1, citations: bool = True, stream: bool = True, model: str = "mistralai/Mixtral-8x7B-Instruct-v0.1"):
+    """
+    Handles a chat request to the Embedchain app.
+    Accepts 'query' and 'session_id' as query parameters.
+    """
+    generator = send_message(query, session_id, number_documents, citations, stream, model)
+    return StreamingResponse(generator)
+
+
+@router.get("/")
+async def root():
+    return responses.RedirectResponse(url="/docs")

api/utils/embedchain.py

@@ -0,0 +1,145 @@
+import asyncio
+import json
+import logging
+import os
+from typing import AsyncIterable
+
+from embedchain import App
+from embedchain.config import BaseLlmConfig
+from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
+from langchain_community.chat_models.huggingface import ChatHuggingFace, HuggingFaceEndpoint
+from langchain.schema import HumanMessage, SystemMessage
+
+# App config using OpenAI gpt-3.5-turbo-1106 as LLM
+'''
+EC_APP_CONFIG = {
+    "app": {
+        "config": {
+            "id": "embedchain-demo-app",
+        }
+    },
+    "llm": {
+        "provider": "openai",
+        "config": {
+            "model": "gpt-3.5-turbo-1106",
+        }
+    },
+    'vectordb': {
+        'provider': 'chroma',
+        'config': {
+            'collection_name': 'rag-full',
+            'dir': 'db',
+            'allow_reset': True
+        }
+    }
+}
+'''
+# Uncomment this configuration to use Mistral as LLM
+
+EC_APP_CONFIG = {
+     "app": {
+         "config": {
+             "name": "embedchain-opensource-app"
+         }
+     },
+     "llm": {
+         "provider": "huggingface",
+         "config": {
+             "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+             "temperature": 0.1,
+             "max_tokens": 250,
+             "top_p": 0.1
+         }
+     },
+     "embedder": {
+         "provider": "huggingface",
+         "config": {
+             "model": "sentence-transformers/all-mpnet-base-v2"
+         }
+     },
+    'vectordb': {
+        'provider': 'chroma',
+        'config': {
+            'collection_name': 'embedchain_store',
+            'dir': 'db',
+            'allow_reset': True
+        }
+    }
+     
+ }
+
+
+
+async def generate_sources_str(sources_metadata):
+    """Generate a string of unique source URLs from the sources metadata."""
+    seen_urls = set()
+    unique_sources = [source for source in sources_metadata if source['url'] not in seen_urls and not seen_urls.add(source['url'])]
+    sources_str = "<sources>\n" + "\n".join(json.dumps(source) for source in unique_sources) + "\n</sources>\n\n"
+    return sources_str
+
+
+async def prepare_contexts_for_llm_query(ec_app, query, config, citations):
+    """Retrieve contexts from the database and prepare them for the LLM query."""
+    contexts = ec_app._retrieve_from_database(input_query=query, config=config, where={"app_id": ec_app.config.id}, citations=citations)
+    if citations and contexts and isinstance(contexts[0], tuple):
+        return [context[0] for context in contexts]
+    return contexts
+
+
+async def generate_messages(ec_app, query, contexts_data_for_llm_query, config):
+    """Generate messages to be used in the LLM query."""
+    messages = []
+    if config.system_prompt:
+        messages.append(SystemMessage(content=config.system_prompt))
+    prompt = ec_app.llm.generate_prompt(query, contexts_data_for_llm_query)
+    messages.append(HumanMessage(content=prompt))
+    return messages
+
+
+async def send_message(query, session_id, number_documents, citations, stream, model) -> AsyncIterable[str]:
+    ec_app = App.from_config(config=EC_APP_CONFIG)
+    context = ec_app.search(query, num_documents=number_documents)
+    sources_str = await generate_sources_str([c['metadata'] for c in context])
+
+    ec_app.llm.update_history(app_id=ec_app.config.id, session_id=session_id)
+    callback = AsyncIteratorCallbackHandler()
+    #config = BaseLlmConfig(model=model, stream=stream, callbacks=[callback], api_key=os.environ["OPENAI_API_KEY"])
+    config = BaseLlmConfig(model=model, stream=stream, callbacks=[callback], api_key=os.environ["HUGGINGFACE_ACCESS_TOKEN"])
+    contexts_data_for_llm_query = await prepare_contexts_for_llm_query(ec_app, query, config, citations)
+    messages = await generate_messages(ec_app, query, contexts_data_for_llm_query, config)
+
+    kwargs = {
+        "model": model,
+        "temperature": config.temperature,
+        "max_tokens": config.max_tokens,
+        "model_kwargs": {"top_p": config.top_p} if config.top_p else {},
+        "streaming": stream,
+        "callbacks": [callback],
+        "api_key": config.api_key,
+        "llm" : HuggingFaceEndpoint(
+            repo_id= model,
+            temperature= 0.1,
+            max_new_tokens= 250,
+            top_p= 0.1,
+            streaming= stream,
+            callbacks= [callback],
+            huggingfacehub_api_token= config.api_key
+        )
+    }
+    
+
+    llm_task = asyncio.create_task(ChatHuggingFace(**kwargs).agenerate(messages=[messages]))
+
+    generated_answer = ""
+    try:
+        yield sources_str
+        async for token in callback.aiter():
+            yield token
+            generated_answer += token
+    except Exception as e:
+        logging.exception(f"Caught exception: {e}")
+    finally:
+        # add conversation in memory
+        ec_app.llm.add_history(ec_app.config.id, query, generated_answer, session_id=session_id)
+        callback.done.set()
+    await llm_task

docker-compose.yml

@@ -0,0 +1,30 @@
+version: '3.9'
+
+services:
+  frontend:
+    build:
+      context: ui/
+      dockerfile: Dockerfile
+    volumes:
+      - ./ui:/app
+      - /app/node_modules
+    ports:
+      - "3000:3000"
+    environment:
+      - NODE_ENV=development
+      - NEXT_PUBLIC_API_ENDPOINT=http://backend:8000
+    depends_on:
+      - backend
+
+  backend:
+    build:
+      context: api/
+      dockerfile: Dockerfile
+    volumes:
+      - ./api:/app
+    env_file:
+      - api/.env
+    ports:
+      - "8010:8000"
+    environment:
+      - PYTHONUNBUFFERED=1

embedchain.json

@@ -0,0 +1,4 @@
+{
+    "name": "rag-full",
+    "provider": "hf/docker"
+}

ui/.env.local

@@ -0,0 +1 @@
+NEXT_PUBLIC_API_ENDPOINT=http://127.0.0.1:8000

ui/.eslintrc.json

@@ -0,0 +1,3 @@
+{
+  "extends": "next/core-web-vitals"
+}

ui/.gitignore

@@ -0,0 +1,32 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts

ui/.next/app-build-manifest.json

@@ -0,0 +1,40 @@
+{
+  "pages": {
+    "/layout": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/css/app/layout.css",
+      "static/chunks/app/layout.js"
+    ],
+    "/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/page.js"
+    ],
+    "/admin/data/add/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/admin/data/add/page.js"
+    ],
+    "/admin/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/admin/page.js"
+    ],
+    "/admin/collections/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/admin/collections/page.js"
+    ],
+    "/admin/collections/[collection_name]/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/admin/collections/[collection_name]/page.js"
+    ],
+    "/search/page": [
+      "static/chunks/webpack.js",
+      "static/chunks/main-app.js",
+      "static/chunks/app/search/page.js"
+    ]
+  }
+}

ui/.next/build-manifest.json

@@ -0,0 +1,30 @@
+{
+  "polyfillFiles": [
+    "static/chunks/polyfills.js"
+  ],
+  "devFiles": [
+    "static/chunks/react-refresh.js"
+  ],
+  "ampDevFiles": [],
+  "lowPriorityFiles": [
+    "static/development/_buildManifest.js",
+    "static/development/_ssgManifest.js"
+  ],
+  "rootMainFiles": [
+    "static/chunks/webpack.js",
+    "static/chunks/main-app.js"
+  ],
+  "pages": {
+    "/_app": [
+      "static/chunks/webpack.js",
+      "static/chunks/main.js",
+      "static/chunks/pages/_app.js"
+    ],
+    "/_error": [
+      "static/chunks/webpack.js",
+      "static/chunks/main.js",
+      "static/chunks/pages/_error.js"
+    ]
+  },
+  "ampFirstPages": []
+}

ui/.next/cache/config.json

@@ -0,0 +1,7 @@
+{
+	"telemetry": {
+		"notifiedAt": "1725586628800",
+		"anonymousId": "7fee4018c383491a5cdd77e2ad22bdc6b6f9b84c0e20e89a45d74e247a1c960a",
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