feat: Implement Pinecone vector store integration

- Update config.py with Pinecone settings and model configurations - Implement VectorStore class with Pinecone backend - Add comprehensive vector operations (add, search, delete) - Set up proper error handling and metadata management - Add .gitignore for Python project
2025-04-16 23:09:52 +01:00
commit 859c17aad8
27 changed files with 2820 additions and 0 deletions
@@ -0,0 +1,101 @@
+import requests
+import json
+import argparse
+
+def test_direct_model(prompt, max_length=200, num_return_sequences=1, temperature=0.7, top_p=0.9):
+    """Test the direct model inference endpoint."""
+    url = "http://localhost:8000/direct-model"
+    
+    payload = {
+        "prompt": prompt,
+        "max_length": max_length,
+        "num_return_sequences": num_return_sequences,
+        "temperature": temperature,
+        "top_p": top_p
+    }
+    
+    print(f"Sending request to {url}")
+    print(f"Payload: {json.dumps(payload, indent=2)}")
+    
+    response = requests.post(url, json=payload)
+    
+    if response.status_code == 200:
+        result = response.json()
+        print("\nResponse:")
+        for i, text in enumerate(result["generated_texts"]):
+            print(f"\n--- Generation {i+1} ---")
+            print(text)
+    else:
+        print(f"Error: {response.status_code}")
+        print(response.text)
+
+def test_generate_copy(prompt, content_type, tone=None, target_audience=None):
+    """Test the generate-copy endpoint."""
+    url = "http://localhost:8000/generate-copy"
+    
+    payload = {
+        "prompt": prompt,
+        "content_type": content_type
+    }
+    
+    if tone:
+        payload["tone"] = tone
+    if target_audience:
+        payload["target_audience"] = target_audience
+    
+    print(f"Sending request to {url}")
+    print(f"Payload: {json.dumps(payload, indent=2)}")
+    
+    response = requests.post(url, json=payload)
+    
+    if response.status_code == 200:
+        result = response.json()
+        print("\nResponse:")
+        print(f"Content: {result['content']}")
+        print(f"Confidence Score: {result['confidence_score']}")
+        print(f"Brand Alignment Score: {result['brand_alignment_score']}")
+    else:
+        print(f"Error: {response.status_code}")
+        print(response.text)
+
+def main():
+    parser = argparse.ArgumentParser(description="Test the backend with the finetuned model")
+    parser.add_argument("--endpoint", type=str, choices=["direct-model", "generate-copy"], default="direct-model",
+                        help="Endpoint to test")
+    parser.add_argument("--prompt", type=str, default="Create a welcome message for new clients",
+                        help="Prompt to generate text for")
+    parser.add_argument("--content-type", type=str, default="email",
+                        help="Content type (for generate-copy endpoint)")
+    parser.add_argument("--tone", type=str, default=None,
+                        help="Tone (for generate-copy endpoint)")
+    parser.add_argument("--target-audience", type=str, default=None,
+                        help="Target audience (for generate-copy endpoint)")
+    parser.add_argument("--max-length", type=int, default=200,
+                        help="Maximum length of the generated text (for direct-model endpoint)")
+    parser.add_argument("--num-return-sequences", type=int, default=1,
+                        help="Number of sequences to generate (for direct-model endpoint)")
+    parser.add_argument("--temperature", type=float, default=0.7,
+                        help="Temperature for sampling (for direct-model endpoint)")
+    parser.add_argument("--top-p", type=float, default=0.9,
+                        help="Top-p for sampling (for direct-model endpoint)")
+    
+    args = parser.parse_args()
+    
+    if args.endpoint == "direct-model":
+        test_direct_model(
+            prompt=args.prompt,
+            max_length=args.max_length,
+            num_return_sequences=args.num_return_sequences,
+            temperature=args.temperature,
+            top_p=args.top_p
+        )
+    else:
+        test_generate_copy(
+            prompt=args.prompt,
+            content_type=args.content_type,
+            tone=args.tone,
+            target_audience=args.target_audience
+        )
+
+if __name__ == "__main__":
+    main()