init file

.gitignore

@@ -0,0 +1,164 @@
+.streamlit/secrets.toml
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+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/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# 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/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

.streamlit/config.toml

@@ -0,0 +1,3 @@
+[secret]
+PINECONE_API_KEY = "595c294f-e189-4051-9023-35461b30dc47"
+GROQ_API_KEY = "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"

LICENSE

@@ -0,0 +1,201 @@
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app.py

@@ -0,0 +1,105 @@
+import streamlit as st
+import os
+import getpass
+import time
+from chatbot_helper import generate, get_docs
+from llama_index.core.llms import ChatMessage
+# from groq import Groq
+from pinecone import Pinecone
+from llama_index.llms.groq import Groq
+from semantic_router.encoders import HuggingFaceEncoder
+
+st.title("🤖 Welcome in :blue[_fam_ _properties_] ChatBot :sunglasses:")
+
+index_name = "fam-rag"
+docs = []
+
+encoder = HuggingFaceEncoder(name="dwzhu/e5-base-4k")
+
+# groq_client = Groq(api_key="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")
+# st.secrets['REPLICATE_API_TOKEN']
+llm = Groq(model="llama3-70b-8192", api_key="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")
+
+# configure client
+pc = Pinecone(api_key="595c294f-e189-4051-9023-35461b30dc47")
+
+index = pc.Index(index_name)
+time.sleep(1)
+
+
+if "messages" not in st.session_state:
+    st.session_state.messages = [
+    
+        ChatMessage(role="system", content="You are a real state assistant that helps users find best properties in Dubai that fit there requirement")
+]
+
+# Display the existing chat messages via `st.chat_message`.
+for message in st.session_state.messages:
+    if message.role != "system":
+        with st.chat_message(message.role):
+            st.markdown(message.content)
+
+# Create a chat input field to allow the user to enter a message. This will display
+# automatically at the bottom of the page.
+if prompt := st.chat_input("What is up?"):
+
+    # Store and display the current prompt.    
+
+    # Generate a response using the OpenAI API.
+    # stream = client.chat.completions.create(
+    #     model="gpt-3.5-turbo",
+    #     messages=[
+    #         {"role": m["role"], "content": m["content"]}
+    #         for m in st.session_state.messages
+    #     ],
+    #     stream=True,
+    # ) 
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    
+    if not prompt.__contains__("Yes") or not prompt.__contains__("No"):
+        docs = get_docs(prompt, 3,encoder, index)
+        docs = [str(i) for i in docs]
+
+        # result = generate(prompt, docs, groq_client, st.session_state.messages)
+
+    docs = "\n---\n".join(docs)
+    
+    system_message =f'''
+        You are a real state assistant act as that and help users find best properties in Dubai that fit there requirement using the
+        context and chat history provided below. 
+        please be precise when you answer the user and get the answer from your history if the question is not related to the context.
+        if you ask the user a yes/no question do not use the provided context for response, use chat history for answer instead.
+    
+        if the context or the chat history may not have the answer of the question get the answer from chat history if not related please
+        ask user to provide you more information
+        \n\n
+        CONTEXT:\n
+        {docs}
+        '''
+    for i, k in enumerate(st.session_state.messages):
+        if k.role =="system":
+            st.session_state.messages[i].content = system_message
+
+    st.session_state.messages.append(ChatMessage(role= "user", content=prompt))
+
+    # generate response
+    # chat_response = groq_client.chat.completions.create(
+    #     model="llama3-70b-8192",
+    #     messages=[
+    #         {"role": m["role"], "content": m["content"]}
+    #         for m in st.session_state.messages
+    #     ],
+    #     stream=True
+    # )
+    resp = llm.stream_chat(st.session_state.messages)
+    print(st.session_state.messages)
+
+    # Stream the response to the chat using `st.write_stream`, then store it in 
+    # session state.
+    print(resp)
+    res = [i.delta for i in resp ]
+    with st.chat_message("assistant"):
+        response = st.write_stream(res)
+
+    st.session_state.messages.append(ChatMessage(role= "assistant", content= "".join([i for i in response])))

chatbot_helper.py

@@ -0,0 +1,39 @@
+def get_docs(question: str, top_k: int, encoder, pinecone_index) -> list[str]:
+    # encode query
+    xq = encoder([question])
+    # search pinecone index
+    res = pinecone_index.query(vector=xq, top_k=top_k, include_metadata=True)
+    # get doc text
+    print(res)
+    docs = [x["metadata"] for x in res["matches"]]
+    return docs
+
+def generate(query: str, docs: list[str], groq_client, messages):
+    docs = "\n---\n".join(docs)
+    system_message =f'''
+        You are a real state assistant that answers questions about properties in Dubai using the
+        context provided below that is you information.
+        then please generate the response like this schema
+        [ANS]
+        ```json
+        {{
+            answer: HERE THE RESPONSE OF LLM
+        }}```
+        [\ANS]
+        if the context may not have the answer of the question please
+        ask user to provide you more information
+        \n\n
+        CONTEXT:\n
+        {docs}
+        '''
+    
+    # generate response
+    chat_response = groq_client.chat.completions.create(
+        model="llama3-70b-8192",
+        messages=messages,
+        stream=True
+    )
+    print(chat_response)
+    for chunk in chat_response:
+        return chunk.choices[0].delta.content
+    # return chat_response.choices[0].message.content

packages.txt

@@ -0,0 +1,6 @@
+--only-upgrade 
+--only-upgrade build-essential
+--only-upgrade pkg-config
+--only-upgrade cmake
+--only-upgrade libpthread-stubs0-dev
+--only-upgrade stdc++

requirements.txt

@@ -0,0 +1,6 @@
+streamlit
+accelerate
+pinecone-client==4.1.0
+semantic-router[local]==0.0.45
+llama-index-llms-groq
+llama-index