init setup

app.py

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+import gradio as gr
+import os
+from dotenv import load_dotenv
+from pinecone import Pinecone
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.prompts import PromptTemplate
+from gemini_integ import GeminiIntegration
+
+# Load environment variables
+
+load_dotenv()
+
+PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
+index_name = "apple-chatbot"
+
+# Initialize Pinecone
+pc = Pinecone(api_key=PINECONE_API_KEY)
+index = pc.Index(index_name)
+
+# Load embeddings
+def load_embeddings():
+    return HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+
+embeddings = load_embeddings()
+
+def get_similarity_search(query_embedding, top_k):
+    search_results = index.query(
+        namespace="ns1",  # Replace with actual namespace
+        vector=query_embedding,
+        top_k=top_k,
+        include_values=True,
+        include_metadata=True
+    )
+    return search_results
+
+# Prompt Template
+prompt_template = PromptTemplate(
+    input_variables=["context", "question"],
+    template="""
+        Helpful Answer for Farmer:
+        Use the following pieces of information to answer the farmer's question about apple orchard management:
+
+        Context: {context}
+        Question: {question}
+
+        If you don't know the answer, say "I'm not sure, but I can try to find more information for you."
+        Only return the helpful answer below and nothing else.
+        Helpful Answer:
+        """
+)
+
+def get_rag_response(query, top_k=2):
+    query_embed = embeddings.embed_query(query)
+    search_res = get_similarity_search(query_embed, top_k=top_k)
+    llm = GeminiIntegration()
+    prompt = prompt_template.format(context=search_res, question=query)
+    response = llm.generate_response(query=prompt)
+    return response
+
+# Gradio Interface
+def chatbot_interface(query):
+    response = get_rag_response(query, top_k=3)
+    return response
+
+# Gradio UI
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""<h1 style='text-align: center; color: #4CAF50;'>🍏 Smart Orchard AI Chatbot 🍏</h1>""")
+    gr.Markdown("""<p style='text-align: center;'>Ask anything about apple cultivation, soil types, pest management, and more!</p>""")
+    
+    with gr.Row():
+        query_input = gr.Textbox(label="Enter Your Query", placeholder="Ask about apple orchard management...")
+        submit_btn = gr.Button("🔍 Search")
+    
+    response_output = gr.Textbox(label="Response", interactive=False)
+    submit_btn.click(chatbot_interface, inputs=query_input, outputs=response_output)
+    
+    gr.Markdown("""<p style='text-align: center;'>Powered by <b>Gemini API</b> and <b>Pinecone Vector Database</b></p>""")
+
+demo.launch()

gemini_integ.py

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+
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+import os
+import google.generativeai as genai
+from dotenv import load_dotenv
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+class GeminiIntegration:
+    """Handles interaction with Google's Gemini API"""
+    
+    def __init__(self, model_name: str = "gemini-2.0-flash", embedding_model: str = "text-embedding-004"):
+        self.model_name = model_name
+        self.embedding_model = embedding_model
+        self._configure_gemini()
+    
+    def _configure_gemini(self):
+        """Configure Gemini API client"""
+        try:
+            api_key = os.getenv("GEMINI_API_KEY")
+            if not api_key:
+                raise ValueError("GEMINI_API_KEY not found in environment variables")
+            genai.configure(api_key=api_key)
+            logger.info("Gemini API configured successfully.")
+        except Exception as e:
+            logger.error(f"Failed to configure Gemini: {str(e)}")
+            raise
+    
+    def generate_response(self, query: str, context: str = "") -> str:
+        """Generate a response from Gemini given a query and optional context"""
+        try:
+            prompt = f"Context: {context}\n\nQuestion: {query}"
+            # prompt checking
+            print("Prompt checking: ")
+            print(prompt)
+
+
+            response = genai.GenerativeModel(self.model_name).generate_content(prompt)
+            return response.text
+        except Exception as e:
+            logger.error(f"Response generation failed: {str(e)}")
+            raise
+    
+    def embed_text(self, text: str):
+        """Generate text embeddings using Gemini"""
+        try:
+            response = genai.embed_content(
+                model=self.embedding_model,
+                content=text,
+                task_type="retrieval_query"
+            )
+            return response['embedding']
+        except Exception as e:
+            logger.error(f"Embedding generation failed: {str(e)}")
+            raise
+
+# example usage
+gem = GeminiIntegration()
+# response = gem.generate_response(query="Tell me about apple cultivation?")
+# print(response)
+
+print("Gemini Integeration working! ")
+

requirements.txt

@@ -0,0 +1,147 @@
+aiofiles==23.2.1
+aiohappyeyeballs==2.4.6
+aiohttp==3.10.11
+aiosignal==1.3.2
+annotated-types==0.7.0
+anyio==4.8.0
+async-timeout==4.0.3
+attrs==25.1.0
+blinker==1.9.0
+cachetools==5.5.2
+certifi==2025.1.31
+cffi==1.17.1
+charset-normalizer==3.4.1
+click==8.1.8
+colorama==0.4.6
+contourpy==1.3.1
+cryptography==44.0.1
+cycler==0.12.1
+dataclasses-json==0.6.7
+exceptiongroup==1.2.2
+fastapi==0.115.8
+ffmpy==0.5.0
+filelock==3.17.0
+Flask==3.1.0
+fonttools==4.56.0
+frozenlist==1.5.0
+fsspec==2025.2.0
+google-ai-generativelanguage==0.6.15
+google-api-core==2.24.1
+google-api-python-client==2.161.0
+google-auth==2.38.0
+google-auth-httplib2==0.2.0
+google-generativeai==0.8.4
+googleapis-common-protos==1.68.0
+gradio==5.17.1
+gradio_client==1.7.1
+greenlet==3.1.1
+grpcio==1.70.0
+grpcio-status==1.70.0
+h11==0.14.0
+httpcore==1.0.7
+httplib2==0.22.0
+httpx==0.28.1
+httpx-sse==0.4.0
+huggingface-hub==0.29.1
+idna==3.10
+iniconfig==2.0.0
+itsdangerous==2.2.0
+Jinja2==3.1.5
+joblib==1.4.2
+jsonpatch==1.33
+jsonpointer==3.0.0
+jwt==1.3.1
+kiwisolver==1.4.8
+langchain==0.3.19
+langchain-community==0.3.18
+langchain-core==0.3.37
+langchain-huggingface==0.1.2
+langchain-pinecone==0.2.3
+langchain-tests==0.3.12
+langchain-text-splitters==0.3.6
+langsmith==0.3.9
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+marshmallow==3.26.1
+matplotlib==3.10.0
+mdurl==0.1.2
+mpmath==1.3.0
+multidict==6.1.0
+mypy-extensions==1.0.0
+networkx==3.4.2
+numpy==1.26.4
+opencv-python==4.11.0.86
+orjson==3.10.15
+packaging==24.2
+pandas==2.2.3
+pillow==11.1.0
+pinecone==5.4.2
+pinecone-client==6.0.0
+pinecone-plugin-inference==3.1.0
+pinecone-plugin-interface==0.0.7
+pluggy==1.5.0
+propcache==0.3.0
+proto-plus==1.26.0
+protobuf==5.29.3
+psutil==7.0.0
+py-cpuinfo==9.0.0
+pyasn1==0.6.1
+pyasn1_modules==0.4.1
+pycparser==2.22
+pydantic==2.10.6
+pydantic-settings==2.8.0
+pydantic_core==2.27.2
+pydub==0.25.1
+Pygments==2.19.1
+pyparsing==3.2.1
+pytesseract==0.3.13
+pytest==8.3.4
+pytest-asyncio==0.25.3
+pytest-socket==0.7.0
+python-dateutil==2.9.0.post0
+python-dotenv==1.0.1
+python-multipart==0.0.20
+pytz==2025.1
+PyYAML==6.0.2
+regex==2024.11.6
+requests==2.32.3
+requests-toolbelt==1.0.0
+rich==13.9.4
+rsa==4.9
+ruff==0.9.7
+safehttpx==0.1.6
+safetensors==0.5.2
+scikit-learn==1.6.1
+scipy==1.15.2
+seaborn==0.13.2
+semantic-version==2.10.0
+sentence-transformers==3.4.1
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+SQLAlchemy==2.0.38
+starlette==0.45.3
+sympy==1.13.1
+syrupy==4.8.2
+tenacity==9.0.0
+threadpoolctl==3.5.0
+tokenizers==0.21.0
+tomli==2.2.1
+tomlkit==0.13.2
+torch==2.6.0
+torchvision==0.21.0
+tqdm==4.67.1
+transformers==4.49.0
+typer==0.15.1
+typing-inspect==0.9.0
+typing_extensions==4.12.2
+tzdata==2025.1
+ultralytics==8.3.78
+ultralytics-thop==2.0.14
+uritemplate==4.1.1
+urllib3==2.3.0
+uvicorn==0.34.0
+websockets==14.2
+Werkzeug==3.1.3
+yarl==1.18.3
+zstandard==0.23.0