Add RAG agent

submodules/moragents_dockers/README.md

@@ -3,7 +3,21 @@
 This repo contains multiple agents and a dapp that enables you to interact with the agents, all running locally and containerized with Docker.
 
 
-## Usage
+
+## Dependencies 
+
+* Docker
+* Ollama
+
+Pull the required models in ollama
+
+```ollama pull llama3```
+
+```ollama pull nomic-embed-text```
+
+
+## Installation
+
 Docker compose will build and run two containers.  One will be for the agents, the other will be for the UI. 
 
 ```docker-compose up```
@@ -44,6 +58,6 @@ A typical flow looks like this:
 - If the user accepts the quote, the swap may proceed.  The back-end will generate transactions which will be sent to the front-end to be signed by the user's wallet.
 - If the allowance for the token being sold is too low, an approval transaction will be generated first
 
+### RAG Agent
 
-
-
+This agent will answer questions about an uploaded PDF file. 

submodules/moragents_dockers/agents/requirements.txt

@@ -6,6 +6,10 @@ scikit-learn
 huggingface-hub
 flask==2.2.2
 Werkzeug==2.2.2
-gradio > /dev/null
 flask-cors
-web3
+web3
+pymupdf==1.22.5
+faiss-cpu
+langchain-text-splitters
+langchain-core
+langchain-community

submodules/moragents_dockers/agents/src/app.py

@@ -3,8 +3,16 @@
 from config import Config
 from swap_agent.src import agent as swap_agent
 from data_agent.src import agent as data_agent
+from rag_agent.src import agent as rag_agent
 from llama_cpp import Llama
 from llama_cpp.llama_tokenizer import LlamaHFTokenizer
+import os 
+import logging
+from langchain_community.llms import Ollama
+from langchain_community.embeddings import OllamaEmbeddings
+from langchain_core.prompts import ChatPromptTemplate
+from rag_agent.src.config import Config as ollama_config
+
 
 
 def load_llm():
@@ -24,6 +32,32 @@ def load_llm():
 app = Flask(__name__)
 CORS(app)
 
+upload_state=False
+UPLOAD_FOLDER = os.path.join(os.getcwd(), 'uploads')
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+app.config['MAX_CONTENT_LENGTH'] = ollama_config.MAX_LENGTH
+
+llm_ollama = Ollama(model="llama3",base_url=ollama_config.URL) 
+embeddings = OllamaEmbeddings(model="nomic-embed-text",base_url=ollama_config.URL)
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+agent =  None
+messages=[]
+prompt = ChatPromptTemplate.from_template(
+    """
+            Answer the following question only based on the given context
+
+            <context>
+            {context}
+            </context>
+
+            Question: {input}
+"""
+)
+
 @app.route('/swap_agent/', methods=['POST'])
 def swap_agent_chat():
     global llm
@@ -67,6 +101,23 @@ def data_agent_messages():
 def data_agent_clear_messages():
     return data_agent.clear_messages()
 
+@app.route('/rag_agent/upload', methods=['POST'])
+def rag_agent_upload():
+    global llm_ollama,UPLOAD_FOLDER,embeddings
+    return rag_agent.upload_file(request, UPLOAD_FOLDER, llm_ollama, embeddings,ollama_config.MAX_FILE_SIZE)
+
+@app.route('/rag_agent/', methods=['POST'])
+def rag_agent_chat():
+    return rag_agent.chat(request)
+
+@app.route('/rag_agent/messages', methods=['GET'])
+def rag_agent_messages():
+    return rag_agent.get_messages()
+
+@app.route('/rag_agent/clear_messages', methods=['GET'])
+def rag_agent_clear_messages():
+    return rag_agent.clear_messages()
+
 
 if __name__ == '__main__':
     app.run(host='0.0.0.0', port=5000, debug=True)

submodules/moragents_dockers/agents/src/config.py

@@ -10,7 +10,7 @@ class Config:
     MODEL_REVISION = "functionary-small-v2.4.Q4_0.gguf"
     MODEL_PATH = "model/"+MODEL_REVISION
     DOWNLOAD_DIR = "model"
-    # Data agent
+    # API endpoints
     COINGECKO_BASE_URL = "https://api.coingecko.com/api/v3"
     DEFILLAMA_BASE_URL = "https://api.llama.fi"
     PRICE_SUCCESS_MESSAGE = "The price of {coin_name} is ${price:,}"
@@ -24,7 +24,6 @@ class Config:
     MARKET_CAP_SUCCESS_MESSAGE = "The market cap of {coin_name} is ${market_cap:,}"
     MARKET_CAP_FAILURE_MESSAGE = "Failed to retrieve market cap. Please enter a valid coin name."
     API_ERROR_MESSAGE = "I can't seem to access the API at the moment."
-    # Swap agent
     INCH_URL = "https://api.1inch.dev/token"
     QUOTE_URL = "https://api.1inch.dev/swap"
     APIBASEURL = f"https://api.1inch.dev/swap/v6.0/"

submodules/moragents_dockers/agents/src/rag_agent/src/agent.py

@@ -0,0 +1,97 @@
+from flask import jsonify
+import os 
+import logging
+from langchain_community.document_loaders import PyMuPDFLoader
+from langchain_community.vectorstores import FAISS
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain.chains.combine_documents import create_stuff_documents_chain
+from langchain.chains import create_retrieval_chain
+from werkzeug.utils import secure_filename
+
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+agent =  None
+messages=[{'role':"assistant","content":"Please upload a file to begin"}]
+upload_state = False
+prompt = ChatPromptTemplate.from_template(
+    """
+            Answer the following question only based on the given context
+
+            <context>
+            {context}
+            </context>
+
+            Question: {input}
+"""
+)
+
+def handle_file_upload(file,UPLOAD_FOLDER,llm,embeddings):
+    global agent,prompt
+    if not os.path.exists(UPLOAD_FOLDER):
+        os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+    filename = secure_filename(file.filename)
+    file.save(os.path.join(UPLOAD_FOLDER, filename))
+    # DocumentToolsGenerator class instantiation 
+    loader = PyMuPDFLoader(os.path.join(UPLOAD_FOLDER,filename))
+    docs = loader.load()
+    text_splitter = RecursiveCharacterTextSplitter()
+    split_documents = text_splitter.split_documents(docs)
+    vector_store = FAISS.from_documents(split_documents, embeddings)
+    docs_chain = create_stuff_documents_chain(llm, prompt)
+    retriever = vector_store.as_retriever()
+    agent = create_retrieval_chain(retriever, docs_chain)
+
+
+def upload_file(request,UPLOAD_FOLDER,llm,embeddings,MAX_SIZE):
+    global upload_state
+    if 'file' not in request.files:
+        return jsonify({'error': 'No file part'}), 400
+    file = request.files['file']
+    if file.filename == '':
+        return jsonify({'error': 'No selected file'}), 400
+    # Check file size
+    file.seek(0, os.SEEK_END)
+    file_length = file.tell()
+    file.seek(0, 0)  # Reset the file pointer to the beginning
+    if file_length > MAX_SIZE:
+        messages.append({"role": "assistant", "content": 'please use a file less than 5 MB'})
+        return jsonify({"role": "assistant", "content": 'please use a file less than 5 MB'})
+    try:
+        handle_file_upload(file,UPLOAD_FOLDER,llm,embeddings)
+        upload_state = True
+        messages.append({"role": "assistant", "content": 'You have successfully uploaded the text'})
+        return jsonify({"role": "assistant", "content": 'You have successfully uploaded the text'})
+    except Exception as e:
+        logging.error(f'Error during file upload: {str(e)}')
+        return jsonify({'error': str(e)}), 500
+
+def chat(request):
+    global messages,upload_state,agent
+    try:
+        data = request.get_json()
+        if 'prompt' in data:
+            prompt = data['prompt']['content']
+            messages.append(data['prompt'])
+            role = "assistant"
+            response = agent.invoke({"input": prompt})  if upload_state else {"answer":"please upload a file first"}
+
+            messages.append({"role": role, "content": response["answer"]})
+            return jsonify({"role": role, "content": response["answer"]})
+        else:
+            return jsonify({"error": "Missing required parameters"}), 400
+    except Exception as e:
+        logging.error(f'Error in chat endpoint: {str(e)}')
+        return jsonify({"Error": str(e)}), 500
+
+def get_messages():
+    global messages
+    return jsonify({"messages": messages})
+
+def clear_messages():
+    global messages
+    messages = [{'role':"assistant","content":"Please upload a file to begin"}]
+    return jsonify({"response": "successfully cleared message history"})
+

submodules/moragents_dockers/agents/src/rag_agent/src/config.py

@@ -0,0 +1,10 @@
+import logging
+
+# Logging configuration
+logging.basicConfig(level=logging.INFO)
+
+# Configuration object
+class Config:
+    MAX_FILE_SIZE=5 * 1024 * 1024  # 5 MB
+    MAX_LENGTH=16 * 1024 * 1024
+    URL="http://host.docker.internal:11434"

submodules/moragents_dockers/docker-compose-apple.yml

@@ -10,7 +10,11 @@ services:
     restart: always
     volumes:
       - agents_data:/var/lib/agents
-      - ./agents/src:/app/src  # Volume for swapagent src
+      - ./agents/src:/app/src
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    environment:
+      - BASE_URL=http://host.docker.internal:11434
 
   nginx:
     build:
@@ -19,6 +23,7 @@ services:
       target: nginx
     ports:
       - '3333:80'
-
+
+
 volumes:
-  agents_data:
+  agents_data:

submodules/moragents_dockers/docker-compose.yml

@@ -10,7 +10,11 @@ services:
     restart: always
     volumes:
       - agents_data:/var/lib/agents
-      - ./agents/src:/app/src  # Volume for swapagent src
+      - ./agents/src:/app/src
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    environment:
+      - BASE_URL=http://host.docker.internal:11434
 
   nginx:
     build:
@@ -21,5 +25,6 @@ services:
       - '3333:80'
 
 
+
 volumes:
   agents_data:

submodules/moragents_dockers/frontend/components/Chat/index.tsx

@@ -162,6 +162,7 @@ export const Chat: FC<ChatProps> = ({
 
         await onSubmitMessage(message, file);
         setMessage('');
+        setFile(null); // Clear the file state after upload
         setShowSpinner(false);
     }
 

submodules/moragents_dockers/frontend/components/SwapAgentModal/index.tsx

@@ -0,0 +1,29 @@
+import { Button, HStack, Modal, ModalBody, ModalCloseButton, ModalContent, ModalFooter, ModalHeader, ModalOverlay, Spacer, Text, useDisclosure } from '@chakra-ui/react';
+import React, { FC, ComponentPropsWithoutRef, useEffect } from 'react';
+
+export interface SwapAgentModalProps extends ComponentPropsWithoutRef<'div'> {
+    isOpen: boolean;
+    onClose: () => void;
+}
+
+export const SwapAgentModal: FC<SwapAgentModalProps> = ({ isOpen, onClose }) => {
+    return (
+        <Modal isCentered onClose={onClose} isOpen={isOpen} motionPreset='slideInBottom' closeOnOverlayClick={false}>
+            <ModalOverlay />
+            <ModalContent sx={{ backgroundColor: '#353936', borderColor: '#313137', color: 'white', borderRadius: '8px', padding: 1 }}>
+                <ModalHeader>Swap Agent</ModalHeader>
+                <ModalBody>
+                    <Text sx={{ fontSize: '16px', lineHeight: '18px' }}>
+                        You have switched to the Swap Agent. Please ensure you have connected your wallet and selected the correct network.
+                    </Text>
+                </ModalBody>
+                <ModalFooter>
+                    <HStack>
+                        <Spacer />
+                        <Button onClick={onClose} variant={'greenCustom'} sx={{ pl: 7, pr: 7 }}>Close</Button>
+                    </HStack>
+                </ModalFooter>
+            </ModalContent>
+        </Modal>
+    );
+};

submodules/moragents_dockers/frontend/config.ts

@@ -28,16 +28,14 @@ export const availableAgents: {
         requirements: {
             connectedWallet: false
         }
-    }
-    /*
+    },
     'rag-agent': {
-        'name': 'Functional Data Agent (RAG FOR FILES)',
-        'description': 'Mock of the Data Agent that supports files',
-        'endpoint': 'http://127.0.0.1:8081',
+        'name': 'PDF Agent',
+        'description': 'Ask questions about an uploaded PDF file',
+        'endpoint': 'http://127.0.0.1:8080/rag_agent',
         requirements: {
             connectedWallet: false
         },
         supportsFiles: true
     }
-    */
 }