add gpt4o test

src/gpt4o_structured.py

@@ -0,0 +1,73 @@
+from io import BytesIO
+from pathlib import Path
+
+from pdf2image import convert_from_path
+
+prompt = """
+This image is an extract from a planning response form filled out by a member of the public. The form may contain typed or handwritten responses, including potentially incomplete or unclear sections. Your task is to extract relevant information in a strict, structured format. Do not repeat the document verbatim. Only output responses in the structured format below.
+
+Instructions:
+1. Extract responses to all structured questions on the form, in the format:
+   {"<question>": "<response>"}
+   
+2. For the handwritten notes under extract them verbatim. If any word is illegible or unclear, use the token <UNKNOWN>. Do not attempt to infer or complete missing parts.
+   
+3. **Do not** output or repeat the original document content in full. Only return structured data in the format described above.
+4. **Ignore irrelevant sections** that are not part of the structured questionnaire or 'Your comments:' section.
+5. If a response is missing or the form section is blank, output:
+   {"<question>": "No response"}
+
+Guidelines:
+- Ensure you return only structured data in JSON-like format.
+- Strictly follow the format for both structured questions and handwritten comments.
+- If any part of the form is unclear or unreadable, do not fill it in with assumptions.
+- Avoid repeating the full content of the form. Focus only on extracting the relevant sections.
+
+Example output:
+{
+  "Do you support the planning proposal?": "Yes",
+  "Your comments:": "The proposal seems reasonable, but <UNKNOWN> needs further assessment."
+}
+"""
+
+images = []
+placeholder = ""
+path = Path("./data/raw/pdfs")
+i = 1
+for file in path.glob("*.pdf"):
+    pdf_images = convert_from_path(file)
+    for image in pdf_images:
+        images.append(image)
+        placeholder += f"<|image_{i}|>\n"
+        i += 1
+
+import base64
+
+buffered = BytesIO()
+images[2].save(buffered, format="JPEG")
+base64_image = base64.b64encode(buffered.getvalue())
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "text",
+                "text": prompt,
+                "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+            }
+        ],
+    }
+]
+import requests
+
+api_key = "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"
+headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
+payload = {"model": "gpt-4o", "messages": messages}
+
+
+response = requests.post(
+    "https://api.openai.com/v1/chat/completions", headers=headers, json=payload
+)
+
+print(response.json()["choices"][0]["message"])

src/planning_ai/phi.py

@@ -76,9 +76,8 @@ prompt = processor.tokenizer.apply_chat_template(
     messages, tokenize=False, add_generation_prompt=True
 )
 
-inputs = processor(prompt, images[0], return_tensors="pt").to("cuda:0")
-
-generation_args = {"max_new_tokens": 1000, "do_sample": False}
+inputs = processor(prompt, images[1], return_tensors="pt").to("cuda:0")
+generation_args = {"max_new_tokens": 10_000}
 
 generate_ids = model.generate(
     **inputs, eos_token_id=processor.tokenizer.eos_token_id, **generation_args