增加多模态模型识别功能，可以进行识别了，程序跑通了

exp_multimodal/ollama_client.py

@@ -1,4 +1,5 @@
 import base64
+import mimetypes
 import os
 import time
 from typing import Any, Dict, List
@@ -11,9 +12,18 @@ DEFAULT_MODEL = os.getenv("VLM_MODEL", "qwen2.5vl:32b")
 
 
 def _img_to_data_uri(path: str) -> str:
+    mime, _ = mimetypes.guess_type(path)
+    if not mime:
+        ext = os.path.splitext(path)[1].lower()
+        if ext in {".jpg", ".jpeg"}:
+            mime = "image/jpeg"
+        elif ext == ".png":
+            mime = "image/png"
+        else:
+            mime = "application/octet-stream"
     with open(path, "rb") as f:
         b64 = base64.b64encode(f.read()).decode("utf-8")
-    return f"data:image/jpeg;base64,{b64}"
+    return f"data:{mime};base64,{b64}"
 
 
 def chat_vision(
@@ -21,7 +31,7 @@ def chat_vision(
     image_paths: List[str],
     *,
     temperature: float = 0.1,
-    options: Dict[str, Any] | None = None,
+    options: Dict[str, Any] | None = None,  # kept for API compatibility, not used in /v1 schema
     model: str = DEFAULT_MODEL,
     timeout_sec: int = 120,
 ) -> str:
@@ -34,39 +44,71 @@ def chat_vision(
             except Exception:
                 img_sizes.append(-1)
         print(
-            f"[Ollama] Prepare chat url={OLLAMA_URL}/api/chat model={model} temp={temperature} "
+            f"[Ollama] Prepare chat url={OLLAMA_URL}/v1/chat/completions model={model} temp={temperature} "
             f"images={len(image_paths)} sizes={img_sizes} timeout={timeout_sec}s"
         )
     except Exception:
         pass
 
-    images = [_img_to_data_uri(p) for p in image_paths]
+    # OpenAI-compatible vision message format: content is a list of parts (text + image_url)
+    content_parts: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
+    for p in image_paths:
+        content_parts.append({
+            "type": "image_url",
+            "image_url": {"url": _img_to_data_uri(p)}
+        })
+
     payload: Dict[str, Any] = {
         "model": model,
         "messages": [
             {
                 "role": "user",
-                "content": prompt,
-                "images": images,
+                "content": content_parts,
             }
         ],
-        "options": {"temperature": temperature, **(options or {})},
+        "temperature": temperature,
         "stream": False,
     }
 
     t0 = time.time()
     try:
-        resp = requests.post(f"{OLLAMA_URL}/api/chat", json=payload, timeout=timeout_sec)
+        resp = requests.post(f"{OLLAMA_URL}/v1/chat/completions", json=payload, timeout=timeout_sec)
         dt = time.time() - t0
         print(f"[Ollama] Response status={resp.status_code} elapsed={dt:.2f}s")
-        resp.raise_for_status()
+        if resp.status_code >= 400:
+            body = resp.text
+            snippet = (body[:400]).replace("\n", " ")
+            print(f"[Ollama][ErrorBody] {snippet}...")
+            resp.raise_for_status()
+
+        # Parse OpenAI-compatible response
+        # Expected: { choices: [ { message: { content: "..." } } ], ... }
         data = resp.json()
-        text = (data.get("message") or {}).get("content", "")
+        if not isinstance(data, dict) or "choices" not in data or not data["choices"]:
+            snippet = (resp.text[:400]).replace("\n", " ")
+            print(f"[Ollama][Error] Unexpected response shape: {snippet}")
+            raise RuntimeError("Unexpected response from /v1/chat/completions")
+
+        choice0 = data["choices"][0]
+        msg = choice0.get("message") or {}
+        text = msg.get("content") or ""
+        if not text:
+            # Some servers might put text in 'choices[0].text' (rare for chat) – try fallback
+            text = choice0.get("text") or ""
         _preview = (text[:120]).replace("\n", " ")
         print(f"[Ollama] Text length={len(text)} preview={_preview}...")
+        if not text:
+            raise RuntimeError("Empty content in choices[0].message.content")
         return text
     except Exception as e:
         dt = time.time() - t0
+        # Print body to help debugging when JSON parsing fails, etc.
+        try:
+            body = resp.text  # type: ignore[name-defined]
+            snippet = (body[:400]).replace("\n", " ")
+            print(f"[Ollama][ErrorBody] {snippet}...")
+        except Exception:
+            pass
         print(f"[Ollama][Error] during request elapsed={dt:.2f}s: {e}")
         raise