Rename llm_utils.py to qa_openrouter.py

llm_utils.py

@@ -1,39 +0,0 @@
-import requests
-import os
-
-OPENROUTER_API = os.getenv("OPENROUTER_API_KEY")
-GROQ_API = os.getenv("GROQ_API_KEY")
-
-def call_llm(prompt, provider="openrouter"):
-    try:
-        if provider == "openrouter" and OPENROUTER_API:
-            resp = requests.post(
-                "https://openrouter.ai/api/v1/chat/completions",
-                headers={"Authorization": f"Bearer {OPENROUTER_API}"},
-                json={"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": prompt}]}
-            )
-            return resp.json()["choices"][0]["message"]["content"]
-        elif provider == "groq" and GROQ_API:
-            resp = requests.post(
-                "https://api.groq.com/openai/v1/chat/completions",
-                headers={"Authorization": f"Bearer {GROQ_API}"},
-                json={"model": "mixtral-8x7b", "messages": [{"role": "user", "content": prompt}]}
-            )
-            return resp.json()["choices"][0]["message"]["content"]
-        else:
-            raise Exception("No valid API keys provided.")
-    except Exception:
-        # failover
-        if provider == "openrouter":
-            return call_llm(prompt, "groq")
-        else:
-            return "⚠️ Could not connect to either API."
-
-def generate_scraper_instruction(user_prompt):
-    system_prompt = f"Given the following user request, extract the main intent and suggest the most relevant website URL and keywords to scrape.\nUser: {user_prompt}"
-    content = call_llm(system_prompt)
-    return {"intent": user_prompt, "url": "https://news.ycombinator.com", "raw_instruction": content}
-
-def answer_query(query, context):
-    qa_prompt = f"Answer the question based on this content:\n\n{context}\n\nQuestion: {query}"
-    return call_llm(qa_prompt)

qa_openrouter.py

@@ -0,0 +1,60 @@
+# qa_openrouter.py
+import os
+import requests
+import json
+from typing import Optional
+
+OPENROUTER_API = "https://openrouter.ai/api/v1/chat/completions"
+
+def ask_openrouter(question: str, context_text: str, model: str = "openrouter/auto") -> str:
+    """
+    Send a chat-style request to OpenRouter.
+    - question: user's natural language question
+    - context_text: scraped data concatenated (we truncate for safety)
+    - model: model id; default uses OpenRouter auto-router
+    """
+    api_key = os.getenv("OPENROUTER_API_KEY")
+    if not api_key:
+        raise RuntimeError("OPENROUTER_API_KEY environment variable not set.")
+
+    # truncate context to avoid huge payloads (approx)
+    MAX_CHARS = 14000
+    ctx = context_text
+    if len(ctx) > MAX_CHARS:
+        ctx = ctx[:MAX_CHARS] + "\n\n[TRUNCATED]"
+
+    system_prompt = (
+        "You are a helpful assistant. Answer questions about the user's scraped web data. "
+        "If the answer requires referring to the data, cite brief snippets. Keep answers concise."
+    )
+
+    # Build messages
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"Here is the scraped content:\n\n{ctx}"},
+        {"role": "user", "content": f"Question: {question}"}
+    ]
+
+    payload = {
+        "model": model,
+        "messages": messages,
+        "max_tokens": 800,
+        "temperature": 0.0
+    }
+
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json"
+    }
+
+    resp = requests.post(OPENROUTER_API, headers=headers, json=payload, timeout=30)
+    if resp.status_code != 200:
+        raise RuntimeError(f"OpenRouter API error {resp.status_code}: {resp.text}")
+    data = resp.json()
+    # OpenRouter responses follow a Chat-completions-like schema: choices[0].message.content
+    try:
+        text = data["choices"][0]["message"]["content"]
+    except Exception:
+        # fallback to raw text
+        text = json.dumps(data, indent=2)
+    return text