update

app.py

@@ -133,7 +133,6 @@ async def generate_text(request: RequestModel):
             generated_text += chunk.choices[0].delta.content
 
     return {"summary_text_2": generated_text}
-    
 @app.post("/generate2/")
 async def generate_text(file: UploadFile = File(...)):
     # Read the uploaded CSV file
@@ -143,20 +142,25 @@ async def generate_text(file: UploadFile = File(...)):
     except Exception as e:
         return {"error": f"Error reading CSV file: {str(e)}"}
 
-    # Assuming you want to generate text based on the CSV data
-    # For demonstration, we'll use the first row of the CSV
-    # Adjust as needed based on your actual requirements
-    text_to_generate = df.iloc[0].to_string()
+    # Concatenate all rows into a single string
+    try:
+        # Convert the entire DataFrame to a string
+        text_to_generate = df.to_string(index=False)
+    except Exception as e:
+        return {"error": f"Error converting DataFrame to string: {str(e)}"}
 
     # Create the request for the API
-    completion = client.chat.completions.create(
-        model="meta/llama-3.1-8b-instruct", 
-        messages=[{"role": "user", "content": prompt1  + text_to_generate}],
-        temperature=0.2,
-        top_p=0.9,
-        # max_tokens=1024, 
-        stream=True
-    )
+    try:
+        completion = client.chat.completions.create(
+            model="meta/llama-3.1-8b-instruct", 
+            messages=[{"role": "user", "content": prompt1  + text_to_generate}],
+            temperature=0.2,
+            top_p=0.9,
+            # max_tokens=1024, 
+            stream=True
+        )
+    except Exception as e:
+        return {"error": f"Error generating text: {str(e)}"}
   
     generated_text = ""
     for chunk in completion: