✅ mock ollama CI/CD and Dockerfile for deployment in hugging face

src/marketingCampaignGen/components/model/generator.py

@@ -36,24 +36,41 @@ Write the campaign in the specified tone and make it persuasive.
 
         self.chain = LLMChain(llm=self.llm, prompt=self.template)
 
-    def generate(self, input_data: dict) -> str:
-        feature_query = ", ".join(input_data["features"])
-        examples = get_similar_examples(feature_query, top_k=2)
-
-        # Flatten list of documents
-        flat_examples = [doc for sublist in examples["documents"] for doc in sublist]
-        example_text = "\n\n".join(flat_examples) if flat_examples else "None"
-
-        # Now pass ALL required fields to the template using `.invoke()` (not `.run()`)
-        response = self.chain.invoke({
-            "product_name": input_data["product_name"],
-            "features": feature_query,
-            "brand": input_data["brand"],
-            "audience": input_data["audience"],
-            "tone": input_data["tone"],
-            "goal": input_data["goal"],
-            "examples": example_text
-        })
-
-        return response["text"]
+    # def generate(self, input_data: dict) -> str:
+    #     feature_query = ", ".join(input_data["features"])
+    #     examples = get_similar_examples(feature_query, top_k=2)
+
+    #     # Flatten list of documents
+    #     flat_examples = [doc for sublist in examples["documents"] for doc in sublist]
+    #     example_text = "\n\n".join(flat_examples) if flat_examples else "None"
+
+    #     response = self.chain.invoke(...).run(
+    #         product_name=input_data["product_name"],
+    #         features=feature_query,
+    #         brand=input_data["brand"],
+    #         audience=input_data["audience"],
+    #         tone=input_data["tone"],
+    #         goal=input_data["goal"],
+    #         # examples=example_text
+    #     )
+
+    #     return response
+    # Adjust path below to the exact module & class where .invoke() is called
+    @patch("src.marketingCampaignGen.components.model.generator.Ollama.invoke")
+    def test_generate_campaign(mock_invoke):
+        mock_invoke.return_value = "Mocked marketing campaign."
+
+        response = client.post("/generate", json=sample_payload)
+
+        print("\n[DEBUG] Status Code:", response.status_code)
+        try:
+            print("[DEBUG] Response JSON:", response.json())
+        except Exception as e:
+            print("[DEBUG] Response could not be parsed:", e)
+            print("[DEBUG] Raw Response Text:", response.text)
+
+        assert response.status_code == 200
+        assert "campaign" in response.json()
+        assert isinstance(response.json()["campaign"], str)
+        assert len(response.json()["campaign"]) > 10