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| import streamlit as st | |
| import os | |
| from google import genai | |
| from google.genai import types | |
| from groq import Groq | |
| # --- Configuration & Styling --- | |
| st.set_page_config(page_title="Gemini 3 + Groq: Hypothesis Engine", layout="wide") | |
| st.title("🔬 Advanced Scientific Hypothesis Engine") | |
| st.caption("Dual-Engine: Gemini 3 for Research | Groq for Speed") | |
| # --- SECURE API KEYS --- | |
| GEMINI_KEY = os.environ.get("gemini_api") | |
| GROQ_KEY = os.environ.get("groq_api") | |
| if not GEMINI_KEY or not GROQ_KEY: | |
| st.error("Please add 'gemini_api' and 'groq_api' to your Secrets.") | |
| st.stop() | |
| # --- Initialize Clients --- | |
| if "gemini_client" not in st.session_state: | |
| st.session_state.gemini_client = genai.Client(api_key=GEMINI_KEY) | |
| if "groq_client" not in st.session_state: | |
| st.session_state.groq_client = Groq(api_key=GROQ_KEY) | |
| SYSTEM_INSTRUCTIONS = "You are a Senior Scientific Discovery Agent. Be precise and ground claims in evidence." | |
| # --- Sidebar: Engine Selection & Research Corpus --- | |
| with st.sidebar: | |
| st.header("⚙️ Engine Settings") | |
| engine = st.radio("Select Primary Brain:", ["Groq (Fast/No Limits)", "Gemini 3 (Deep Search/Code)"]) | |
| st.header("📚 Research Corpus") | |
| uploaded_files = st.file_uploader("Upload PDFs", type="pdf", accept_multiple_files=True) | |
| if st.button("Reset Lab State"): | |
| for key in list(st.session_state.keys()): | |
| del st.session_state[key] | |
| st.rerun() | |
| # --- Initialize Messages --- | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| # --- Main Interaction Loop --- | |
| for msg in st.session_state.messages: | |
| with st.chat_message(msg["role"]): | |
| st.markdown(msg["content"]) | |
| if prompt := st.chat_input("Enter your research objective..."): | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| with st.chat_message("assistant"): | |
| if engine == "Groq (Fast/No Limits)": | |
| with st.spinner("Groq is thinking..."): | |
| chat_completion = st.session_state.groq_client.chat.completions.create( | |
| messages=[{"role": "user", "content": prompt}], | |
| model="llama-3.3-70b-versatile", | |
| ) | |
| response_text = chat_completion.choices[0].message.content | |
| st.markdown(response_text) | |
| else: | |
| with st.status("Gemini 3 Researching...", expanded=True) as status: | |
| try: | |
| config = types.GenerateContentConfig( | |
| system_instruction=SYSTEM_INSTRUCTIONS, | |
| thinking_config=types.ThinkingConfig(include_thoughts=True, thinking_level=types.ThinkingLevel.LOW), | |
| tools=[types.Tool(google_search=types.GoogleSearchRetrieval()), types.Tool(code_execution=types.ToolCodeExecution())] | |
| ) | |
| # Send message using Gemini | |
| response = st.session_state.gemini_client.models.generate_content( | |
| model="gemini-3-flash-preview", | |
| contents=prompt, | |
| config=config | |
| ) | |
| # Display Reasoning/Code | |
| for part in response.candidates[0].content.parts: | |
| if part.thought: | |
| st.info(f"**Reasoning:** {part.text}") | |
| if part.executable_code: | |
| st.code(part.executable_code.code, language="python") | |
| response_text = response.text | |
| st.markdown(response_text) | |
| status.update(label="Research Complete", state="complete") | |
| except Exception as e: | |
| st.error(f"Gemini Error: {e}") | |
| response_text = "Error occurred." | |
| st.session_state.messages.append({"role": "assistant", "content": response_text}) |