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README.md

@@ -1,13 +1,12 @@
 ---
-title: Nagpur FoodGPT
-emoji: 🚀
-colorFrom: indigo
-colorTo: gray
+title: NagpurFoodGPT! 
+emoji: 🍊
+colorFrom: #FF5733
+colorTo: #FFBF00
 sdk: streamlit
-sdk_version: 1.27.2
+sdk_version: 1.25.0
 app_file: app.py
 pinned: false
-license: llama2
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+

app.py

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+import streamlit as st
+from streamlit_chat import message
+from langchain.chains import ConversationalRetrievalChain
+from langchain.document_loaders import DirectoryLoader
+from langchain.document_loaders import PyPDFLoader 
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.llms import CTransformers
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import FAISS
+from langchain.memory import ConversationBufferMemory
+from langchain.document_loaders.csv_loader import CSVLoader
+import requests
+from PIL import Image
+import pydeck as pdk
+import os
+import json
+
+st.set_page_config(
+   page_title="FoodGPT - Nagpur Based Food Recommendation System.",
+   page_icon="🍊",
+   layout="wide",
+   initial_sidebar_state="expanded",
+)
+
+from langchain.document_loaders.csv_loader import CSVLoader
+loader = CSVLoader(file_path='data.csv')
+documents = loader.load()
+
+text_splitter  = RecursiveCharacterTextSplitter(chunk_size=500,chunk_overlap=50)
+text_chunks = text_splitter.split_documents(documents)
+
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2",
+                                   model_kwargs={'device':"cpu"})
+
+vector_store = FAISS.from_documents(text_chunks,embeddings)
+
+llm = CTransformers(model="llama-2-7b-chat.ggmlv3.q4_0.bin",model_type="llama",
+                    config={'max_new_tokens':128,'temperature':0.01})
+
+memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+
+chain = ConversationalRetrievalChain.from_llm(llm=llm,chain_type='stuff',
+                                              retriever=vector_store.as_retriever(search_kwargs={"k":2}),
+                                              memory=memory)
+
+# Sidebar for user input
+st.sidebar.title("FoodGPT!🍊")
+st.sidebar.info("FoodGPT : A Nagpur Based Food Recommendation Chat! Recommends you the best locally recognized brands for your cravings! As this system is backed with LLMA-2 on hand picked data.")
+github_link = "[GitHub]()"
+st.sidebar.info("To contribute and Sponser - " + github_link)
+
+st.title("FoodGPT: A Nagpur based Food Recommendation Bot! 🍊")
+
+if 'history' not in st.session_state:
+    st.session_state['history'] = []
+
+if 'generated' not in st.session_state:
+    st.session_state['generated'] = ["Hello!I'm FoodGPT, Ask me anything about Nagpur's Food."]
+
+if 'past' not in st.session_state:
+    st.session_state['past'] = ["Hello!"]
+
+reply_container = st.container()
+container = st.container()
+
+with container:
+    with st.form(key='my_form', clear_on_submit=True):
+        user_input = st.text_input("Question:", placeholder="Ask anything about Nagpur's Food Joints or cravings", key='input')
+        image_upload = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+        submit_button = st.form_submit_button(label='Send')
+
+    try:
+        if submit_button and user_input:
+            output = chain({"question": user_input, "chat_history": st.session_state['history']})["answer"]
+            st.session_state['past'].append(user_input)
+            st.session_state['generated'].append(output)
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+
+if st.session_state['generated']:
+    with reply_container:
+        for i in range(len(st.session_state['generated'])):
+            message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="thumbs")
+            message(st.session_state["generated"][i], key=str(i), avatar_style="fun-emoji")
+
+
+API_URL = "https://api-inference.huggingface.co/models/Prasanna18/indian-food-classification"
+HEADERS = {"Authorization": "Bearer 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"}
+
+def query_image_classification(image_bytes):
+    try:
+        response = requests.post(API_URL, headers=HEADERS, data=image_bytes)
+        result = response.json()
+        return result
+    except Exception as e:
+        st.error(f"An error occurred during image classification: {str(e)}")
+        return None
+
+if image_upload:
+    image_bytes = image_upload.read()
+    
+    classification_result = query_image_classification(image_bytes)
+    
+    if classification_result:
+        st.image(image_upload, caption="Uploaded Image", use_column_width=True)
+        
+        if isinstance(classification_result, list) and classification_result:
+            # Ensure that classification_result is a list of results and not empty
+            best_label = max(classification_result, key=lambda x: x.get('score', 0))
+            
+            if 'label' in best_label:
+                st.header("Image Classification Result:")
+                st.write(f"Classified as: {best_label['label']}")
+            else:
+                st.error("Invalid classification result format. Missing 'label' key.")
+        else:
+            st.error("Invalid classification result format or empty result list.")
+    else:
+        st.error("No classification result received.")
+
+
+import pydeck as pdk
+
+st.title("Nagpur Map")
+center = [21.1458, 79.0882]
+
+st.pydeck_chart(
+    pdk.Deck(
+        map_style="mapbox://styles/mapbox/light-v9",
+        initial_view_state={
+            "latitude": center[0],
+            "longitude": center[1],
+            "zoom": 13,
+            "pitch": 10,
+        },
+        layers=[
+            pdk.Layer(
+                "ScatterplotLayer",
+                data=[{"position": center, "tooltip": "Nagpur"}],
+                get_position="position",
+                get_radius=10000,
+                get_color=[255, 0, 0],
+                pickable=True,
+            ),
+        ],
+    )
+)
+
+

cached_data.json

@@ -0,0 +1 @@
+{"vector_store": 

llama-2-7b-chat.ggmlv3.q4_0 10.47.24 AM.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8daa9615cce30c259a9555b1cc250d461d1bc69980a274b44d7eda0be78076d8
+size 3791725184

requirements.txt

@@ -0,0 +1,191 @@
+absl-py==1.4.0
+accelerate==0.21.0
+aiofiles==23.2.1
+aiohttp==3.8.5
+aiosignal==1.3.1
+altair==5.0.1
+anyio==3.6.2
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.1.0
+bitsandbytes==0.40.2
+blinker==1.6.2
+blis==0.7.10
+branca==0.6.0
+cachetools==5.3.1
+catalogue==2.0.9
+certifi==2023.5.7
+charset-normalizer==3.1.0
+click==8.1.3
+colorama==0.4.6
+confection==0.1.1
+contourpy==1.1.0
+ctransformers==0.2.27
+cycler==0.11.0
+cymem==2.0.7
+dataclasses-json==0.6.1
+datasets==2.14.4
+dill==0.3.7
+docopt==0.6.2
+exceptiongroup==1.1.2
+faiss-cpu==1.7.4
+fake-useragent==1.1.3
+fastapi==0.95.2
+ffmpy==0.3.1
+filelock==3.12.2
+Flask==2.3.2
+flatbuffers==23.5.26
+folium==0.14.0
+fonttools==4.42.0
+frozenlist==1.4.0
+fsspec==2023.6.0
+gast==0.4.0
+gitdb==4.0.10
+GitPython==3.1.37
+google-auth==2.17.3
+google-auth-oauthlib==1.0.0
+google-pasta==0.2.0
+gradio==3.40.1
+gradio_client==0.4.0
+grpcio==1.57.0
+h11==0.14.0
+h5py==3.9.0
+httpcore==0.17.3
+httpx==0.24.1
+huggingface-hub==0.16.4
+idna==3.4
+importlib-metadata==6.8.0
+importlib-resources==6.0.1
+install==1.3.5
+itsdangerous==2.1.2
+Jinja2==3.1.2
+joblib==1.2.0
+jsonify==0.5
+jsonpatch==1.33
+jsonpointer==2.4
+jsonschema==4.19.0
+jsonschema-specifications==2023.7.1
+keras==2.13.1
+kiwisolver==1.4.4
+langchain==0.0.309
+langcodes==3.3.0
+langsmith==0.0.42
+libclang==16.0.6
+linkify-it-py==2.0.2
+Markdown==3.4.4
+markdown-it-py==2.2.0
+MarkupSafe==2.1.2
+marshmallow==3.20.1
+matplotlib==3.7.2
+mdit-py-plugins==0.3.3
+mdurl==0.1.2
+mpmath==1.3.0
+multidict==6.0.4
+multiprocess==0.70.15
+murmurhash==1.0.9
+mypy-extensions==1.0.0
+networkx==3.1
+nltk==3.8.1
+numpy==1.24.3
+oauthlib==3.2.2
+openai==0.27.9
+opencv-python==4.8.0.76
+opt-einsum==3.3.0
+orjson==3.9.5
+outcome==1.2.0
+packaging==23.1
+pandas==2.0.3
+pathy==0.10.2
+peft==0.4.0
+Pillow==10.0.0
+preshed==3.0.8
+protobuf==4.24.1
+psutil==5.9.5
+py-cpuinfo==9.0.0
+pyarrow==13.0.0
+pyasn1==0.5.0
+pyasn1-modules==0.3.0
+pydantic==1.10.8
+pydeck==0.8.1b0
+pydub==0.25.1
+Pygments==2.16.1
+pyparsing==3.0.9
+pypdf==3.16.2
+PySocks==1.7.1
+python-dateutil==2.8.2
+python-decouple==3.8
+python-multipart==0.0.6
+pytz==2023.3
+PyYAML==6.0.1
+referencing==0.30.2
+regex==2023.8.8
+requests==2.31.0
+requests-oauthlib==1.3.1
+requests-toolbelt==1.0.0
+rich==13.6.0
+rpds-py==0.9.2
+rsa==4.9
+safetensors==0.3.2
+scikit-learn==1.2.2
+scipy==1.10.1
+seaborn==0.12.2
+selenium==4.10.0
+semantic-version==2.10.0
+sentence-transformers==2.2.2
+sentencepiece==0.1.99
+six==1.16.0
+smart-open==6.3.0
+smmap==5.0.1
+sniffio==1.3.0
+sortedcontainers==2.4.0
+spacy==3.6.1
+spacy-legacy==3.0.12
+spacy-loggers==1.0.4
+SQLAlchemy==2.0.21
+srsly==2.4.7
+starlette==0.27.0
+streamlit==1.27.1
+streamlit-chat==0.1.1
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard==2.13.0
+tensorboard-data-server==0.7.1
+tensorflow==2.13.0
+tensorflow-estimator==2.13.0
+tensorflow-macos==2.13.0
+termcolor==2.3.0
+thinc==8.1.12
+threadpoolctl==3.1.0
+tiktoken==0.5.1
+tokenizers==0.13.3
+toml==0.10.2
+toolz==0.12.0
+torch==2.0.1
+torch-tb-profiler==0.4.1
+torchaudio==2.0.2
+torchvision==0.15.2
+tornado==6.3.3
+tqdm==4.65.0
+transformers==4.31.0
+trio==0.22.1
+trio-websocket==0.10.3
+trl==0.4.7
+typer==0.9.0
+typing-inspect==0.9.0
+typing_extensions==4.5.0
+tzdata==2023.3
+tzlocal==5.0.1
+uc-micro-py==1.0.2
+ultralytics==8.0.188
+urllib3==2.0.2
+uvicorn==0.22.0
+validators==0.22.0
+wasabi==1.1.2
+websockets==11.0.3
+Werkzeug==2.3.4
+wrapt==1.15.0
+wsproto==1.2.0
+xxhash==3.3.0
+yarl==1.9.2
+zipp==3.17.0