Upload folder using huggingface_hub

main.py

@@ -4,14 +4,89 @@ import os
 from dotenv import load_dotenv
 import gradio as gr
 import google.generativeai as genai
+import json
 load_dotenv()
 genai.configure(api_key=os.getenv('API_KEY'))
 model = genai.GenerativeModel('gemini-1.5-flash') 
+PRODUCT_HUNT_BASE_URL = "https://api.producthunt.com/v2/api/graphql"
 
+def fetch_product_hunt_posts(industry, product_type):
+    """Fetches the top 10 Product Hunt posts matching the given industry and product type."""
+
+    developer_token = os.getenv("PRODUCT_HUNT_DEVELOPER_TOKEN")
+
+    
+
+    query = """
+    query {
+      posts(first: 30, order: VOTES) { # Fetch 30 posts
+        edges {
+          node {
+            id
+            name
+            tagline
+            votesCount
+            website
+            commentsCount
+          }
+        }
+      }
+    }
+    """
+
+    headers = {"Authorization": f"Bearer {developer_token}"}
+    response = requests.post(
+        PRODUCT_HUNT_BASE_URL,
+        json={"query": query},  
+        headers=headers
+    )
+    response.raise_for_status()
+
+    try:
+        data = response.json()
+        print(json.dumps(data, indent=2))  
+
+        posts = [edge["node"] for edge in data["data"]["posts"]["edges"]]
+
+        # Filter by industry and product type (case-insensitive)
+        filtered_posts = [
+            post 
+            for post in posts 
+            if industry.lower() in post["tagline"].lower() 
+            and product_type.lower() in post["tagline"].lower()
+        ]
+
+        # Limit to top 3 filtered posts
+        top_filtered_posts = filtered_posts[:3]
+
+        return top_filtered_posts 
+
+    except KeyError:
+        print("Unexpected API response format.")
+        return []
 def generate_product_ideas(industry, product_type, target_audience, features, constraints):
-    prompt = f"Generate innovative product ideas for the {industry} industry. The product should be a {product_type} targeting {target_audience}. It should have the following features: {features}. Consider these constraints: {constraints}."
+  
+    product_hunt_posts = fetch_product_hunt_posts(industry, product_type)
+
+    top_products = ", ".join([post["name"] for post in product_hunt_posts[:3]])
+    summary = f"Top products in the {industry} {product_type} category include: {top_products}"
+
+    prompt = f"""
+    Generate innovative product ideas with these details:
+
+    Industry: {industry}
+    Product Type: {product_type}
+    Target Audience: {target_audience}
+    Desired Features: {features if features else "N/A"}
+    Constraints: {constraints if constraints else "N/A"}
+
+    Market Analysis (Product Hunt):
+    {summary}
+
+    Provide a concise list of product ideas, each with a brief description.
+    """
+
     response = model.generate_content(prompt)
-    print(response.text)
     return response.text
   
    

product_hunt

@@ -0,0 +1,60 @@
+import requests
+import os
+import json
+from dotenv import load_dotenv
+
+load_dotenv()
+
+PRODUCT_HUNT_BASE_URL = "https://api.producthunt.com/v2/api/graphql"
+
+def fetch_product_hunt_posts(industry, product_type):
+    """Fetches the top 10 Product Hunt posts matching the given industry and product type."""
+
+    developer_token = os.getenv("PRODUCT_HUNT_DEVELOPER_TOKEN")
+
+    # Updated GraphQL Query
+    query = """
+    query {
+      posts(first: 10, order: VOTES) {
+        edges {
+          node {
+            id
+            name
+            tagline
+            votesCount
+            website
+            commentsCount
+          }
+        }
+      }
+    }
+    """
+
+    # Send GraphQL Request (No filter variable)
+    headers = {"Authorization": f"Bearer {developer_token}"}
+    response = requests.post(
+        PRODUCT_HUNT_BASE_URL,
+        json={"query": query},  
+        headers=headers
+    )
+    response.raise_for_status()
+
+    # Process Results
+    try:
+        data = response.json()
+        print(json.dumps(data, indent=2))  # Print raw data for debugging
+
+        posts = [edge["node"] for edge in data["data"]["posts"]["edges"]]
+        return posts
+    except KeyError:
+        print("Unexpected API response format.")
+        return []
+
+
+
+# Example Usage:
+if __name__ == "__main__":
+    industry = "tech"
+    product_type = "saas"
+    posts = fetch_product_hunt_posts(industry, product_type)
+    print(json.dumps(posts, indent=2))

requirements.txt

@@ -0,0 +1,84 @@
+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==4.4.0
+beautifulsoup4==4.12.3
+cachetools==5.4.0
+certifi==2024.7.4
+charset-normalizer==3.3.2
+click==8.1.7
+contourpy==1.2.1
+cycler==0.12.1
+dnspython==2.6.1
+email_validator==2.2.0
+fastapi==0.111.1
+fastapi-cli==0.0.4
+ffmpy==0.3.2
+filelock==3.15.4
+fonttools==4.53.1
+fsspec==2024.6.1
+google==3.0.0
+google-ai-generativelanguage==0.6.6
+google-api-core==2.19.1
+google-api-python-client==2.138.0
+google-auth==2.32.0
+google-auth-httplib2==0.2.0
+google-generativeai==0.7.2
+googleapis-common-protos==1.63.2
+gradio==4.39.0
+gradio_client==1.1.1
+grpcio==1.65.1
+grpcio-status==1.62.2
+h11==0.14.0
+httpcore==1.0.5
+httplib2==0.22.0
+httptools==0.6.1
+httpx==0.27.0
+huggingface-hub==0.24.3
+idna==3.7
+importlib_resources==6.4.0
+Jinja2==3.1.4
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.9.1
+mdurl==0.1.2
+numpy==2.0.1
+orjson==3.10.6
+packaging==24.1
+pandas==2.2.2
+pillow==10.4.0
+proto-plus==1.24.0
+protobuf==4.25.4
+pyasn1==0.6.0
+pyasn1_modules==0.4.0
+pydantic==2.8.2
+pydantic_core==2.20.1
+pydub==0.25.1
+Pygments==2.18.0
+pyparsing==3.1.2
+python-dateutil==2.9.0.post0
+python-dotenv==1.0.1
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML==6.0.1
+requests==2.32.3
+rich==13.7.1
+rsa==4.9
+ruff==0.5.5
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.1
+soupsieve==2.5
+starlette==0.37.2
+tomlkit==0.12.0
+tqdm==4.66.4
+typer==0.12.3
+typing_extensions==4.12.2
+tzdata==2024.1
+uritemplate==4.1.1
+urllib3==2.2.2
+uvicorn==0.30.3
+uvloop==0.19.0
+watchfiles==0.22.0
+websockets==11.0.3