WhatsApp Chat Bot Developer - Upwork
Entry Point: Create a QR code for farmers to scan and gain access to the WhatsApp chatbot. Chat Session Initiation: When the QR code is scanned, the farmer lands on the WhatsApp chat window, and a chat session is initiated. LLM Model Selection: Discover and choose an LLM model that connects with WhatsApp APIs and acts as a bot to respond to the farmer's queries. Ensure it can understand and respond in Hindi, English, and Hinglish. Multilingual Capabilities: Ensure the LLM models are conversant and comprehensive in understanding and responding in Hindi, English, and Hinglish. Backend Logic and DB Operations: The LLM APIs will connect with backend logic to connect to the database and perform CRUD and Fetch operations on the DB. Database Setup for Farmers: Create a table/record in the database for Farmers with fields like Farmer Name, Location, Salary, Crop Preferences, Machinery Needed, and Pesticides. User Profile Creation: Create a user profile table/collection in the backend to store details such as farmer's name, location, salary, crop preferences, machinery needed, and pesticides required. User Data Collection: Create 2 records/documents for the Farmer Table/Collection in the backend in SQL/NoSQL DB (e.g., MongoDB). User Identification: When a farmer initiates a chat, check if they are a returning user or a new user. If they are a new user, collect their location and salary details. Weather Data Integration: Use a weather API to fetch the current weather based on the farmer's location. Crop Recommendations: Based on the weather data and salary, recommend suitable crops for the farmer's location. Machinery and Pesticides Recommendations: Ask if the farmer needs machinery or pesticides. Based on their requirements, recommend machinery and pesticides. Order Placement: If the farmer wants to order, let them specify what they need. Select items from the database based on the farmer's requirements and create a list of those items with details such as name, picture, size, and price. Sorting and Display: Sort the list of items based on the best price and proximity to the farmer's location. Display the items in sets of 4 in a 2x2 grid format with details: Item Picture, Item Name, Size, Price, and Supplier Name. View More Option: Provide an option for the farmer to view more items. Item Selection: Allow the farmer to select items in various ways (e.g., specifying quantities or clicking on items). Create a cache queue of selected items at the backend to update the Temp Order Table/Document. Ambiguous Selections: If the selection is unclear, ask for clarification and display the relevant items again. Latent Response Handling: If the farmer is slow to respond, prompt them to continue or finalize their order. Complementary Recommendations: Suggest additional items that complement the selected ones. Order Confirmation: Once the farmer finalizes the selection, summarize the order and ask for confirmation. Order Editing: If the farmer wants to edit the order, allow them to make changes and update the Temp Order Table accordingly. Final Confirmation: After editing, confirm the order again. Streamlit Link for Government Schemes: After crop recommendations, provide a link to a Streamlit web app that displays available government schemes for farmers. Sending YouTube Instruction Links: If the farmer needs recommendations on how to grow the required crop, send YouTube instructional links based on their preferences. Order Completion: Send the final confirmed order details to the farmer on WhatsApp and store the order details in the database. Dashboard: Create a backend dashboard to view user, order, and item data with timestamps. Skills required: - Chatbot development - Artificial intelligence - API integration - DatabaseBudget: $120 Posted On: June 30, 2024 08:51 UTCCategory: Generative AI ModelingSkills:Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database Skills: Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database Country: India click to apply
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Entry Point:
Create a QR code for farmers to scan and gain access to the WhatsApp chatbot.
Chat Session Initiation:
When the QR code is scanned, the farmer lands on the WhatsApp chat window, and a chat session is initiated.
LLM Model Selection:
Discover and choose an LLM model that connects with WhatsApp APIs and acts as a bot to respond to the farmer's queries. Ensure it can understand and respond in Hindi, English, and Hinglish.
Multilingual Capabilities:
Ensure the LLM models are conversant and comprehensive in understanding and responding in Hindi, English, and Hinglish.
Backend Logic and DB Operations:
The LLM APIs will connect with backend logic to connect to the database and perform CRUD and Fetch operations on the DB.
Database Setup for Farmers:
Create a table/record in the database for Farmers with fields like Farmer Name, Location, Salary, Crop Preferences, Machinery Needed, and Pesticides.
User Profile Creation:
Create a user profile table/collection in the backend to store details such as farmer's name, location, salary, crop preferences, machinery needed, and pesticides required.
User Data Collection:
Create 2 records/documents for the Farmer Table/Collection in the backend in SQL/NoSQL DB (e.g., MongoDB).
User Identification:
When a farmer initiates a chat, check if they are a returning user or a new user.
If they are a new user, collect their location and salary details.
Weather Data Integration:
Use a weather API to fetch the current weather based on the farmer's location.
Crop Recommendations:
Based on the weather data and salary, recommend suitable crops for the farmer's location.
Machinery and Pesticides Recommendations:
Ask if the farmer needs machinery or pesticides.
Based on their requirements, recommend machinery and pesticides.
Order Placement:
If the farmer wants to order, let them specify what they need.
Select items from the database based on the farmer's requirements and create a list of those items with details such as name, picture, size, and price.
Sorting and Display:
Sort the list of items based on the best price and proximity to the farmer's location.
Display the items in sets of 4 in a 2x2 grid format with details: Item Picture, Item Name, Size, Price, and Supplier Name.
View More Option:
Provide an option for the farmer to view more items.
Item Selection:
Allow the farmer to select items in various ways (e.g., specifying quantities or clicking on items).
Create a cache queue of selected items at the backend to update the Temp Order Table/Document.
Ambiguous Selections:
If the selection is unclear, ask for clarification and display the relevant items again.
Latent Response Handling:
If the farmer is slow to respond, prompt them to continue or finalize their order.
Complementary Recommendations:
Suggest additional items that complement the selected ones.
Order Confirmation:
Once the farmer finalizes the selection, summarize the order and ask for confirmation.
Order Editing:
If the farmer wants to edit the order, allow them to make changes and update the Temp Order Table accordingly.
Final Confirmation:
After editing, confirm the order again.
Streamlit Link for Government Schemes:
After crop recommendations, provide a link to a Streamlit web app that displays available government schemes for farmers.
Sending YouTube Instruction Links:
If the farmer needs recommendations on how to grow the required crop, send YouTube instructional links based on their preferences.
Order Completion:
Send the final confirmed order details to the farmer on WhatsApp and store the order details in the database.
Dashboard:
Create a backend dashboard to view user, order, and item data with timestamps.
Skills required:
- Chatbot development
- Artificial intelligence
- API integration
- Database
Budget: $120
Posted On: June 30, 2024 08:51 UTC
Category: Generative AI Modeling
Skills:Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database
Skills: Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database
Country: India
click to apply
Create a QR code for farmers to scan and gain access to the WhatsApp chatbot.
Chat Session Initiation:
When the QR code is scanned, the farmer lands on the WhatsApp chat window, and a chat session is initiated.
LLM Model Selection:
Discover and choose an LLM model that connects with WhatsApp APIs and acts as a bot to respond to the farmer's queries. Ensure it can understand and respond in Hindi, English, and Hinglish.
Multilingual Capabilities:
Ensure the LLM models are conversant and comprehensive in understanding and responding in Hindi, English, and Hinglish.
Backend Logic and DB Operations:
The LLM APIs will connect with backend logic to connect to the database and perform CRUD and Fetch operations on the DB.
Database Setup for Farmers:
Create a table/record in the database for Farmers with fields like Farmer Name, Location, Salary, Crop Preferences, Machinery Needed, and Pesticides.
User Profile Creation:
Create a user profile table/collection in the backend to store details such as farmer's name, location, salary, crop preferences, machinery needed, and pesticides required.
User Data Collection:
Create 2 records/documents for the Farmer Table/Collection in the backend in SQL/NoSQL DB (e.g., MongoDB).
User Identification:
When a farmer initiates a chat, check if they are a returning user or a new user.
If they are a new user, collect their location and salary details.
Weather Data Integration:
Use a weather API to fetch the current weather based on the farmer's location.
Crop Recommendations:
Based on the weather data and salary, recommend suitable crops for the farmer's location.
Machinery and Pesticides Recommendations:
Ask if the farmer needs machinery or pesticides.
Based on their requirements, recommend machinery and pesticides.
Order Placement:
If the farmer wants to order, let them specify what they need.
Select items from the database based on the farmer's requirements and create a list of those items with details such as name, picture, size, and price.
Sorting and Display:
Sort the list of items based on the best price and proximity to the farmer's location.
Display the items in sets of 4 in a 2x2 grid format with details: Item Picture, Item Name, Size, Price, and Supplier Name.
View More Option:
Provide an option for the farmer to view more items.
Item Selection:
Allow the farmer to select items in various ways (e.g., specifying quantities or clicking on items).
Create a cache queue of selected items at the backend to update the Temp Order Table/Document.
Ambiguous Selections:
If the selection is unclear, ask for clarification and display the relevant items again.
Latent Response Handling:
If the farmer is slow to respond, prompt them to continue or finalize their order.
Complementary Recommendations:
Suggest additional items that complement the selected ones.
Order Confirmation:
Once the farmer finalizes the selection, summarize the order and ask for confirmation.
Order Editing:
If the farmer wants to edit the order, allow them to make changes and update the Temp Order Table accordingly.
Final Confirmation:
After editing, confirm the order again.
Streamlit Link for Government Schemes:
After crop recommendations, provide a link to a Streamlit web app that displays available government schemes for farmers.
Sending YouTube Instruction Links:
If the farmer needs recommendations on how to grow the required crop, send YouTube instructional links based on their preferences.
Order Completion:
Send the final confirmed order details to the farmer on WhatsApp and store the order details in the database.
Dashboard:
Create a backend dashboard to view user, order, and item data with timestamps.
Skills required:
- Chatbot development
- Artificial intelligence
- API integration
- Database
Budget: $120
Posted On: June 30, 2024 08:51 UTC
Category: Generative AI Modeling
Skills:Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database
Skills: Chatbot Development, Bot Development, Chat & Messaging Software, JavaScript, API, Artificial Intelligence, Database
Country: India
click to apply
