Upload 2 files
Browse files- app.py +23 -24
- requirements.txt +3 -1
app.py
CHANGED
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@@ -9,7 +9,8 @@ import gradio as gr
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from dateutil import parser as dateparser
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from fastapi import FastAPI
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from pydantic import BaseModel
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from analytics import record_request, last_n_days_df, last_n_days_avg_time_df
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# --- Prompts ---
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@@ -71,12 +72,11 @@ async def search_web_logic(query: str, serper_api_key: str, search_type: str, nu
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except Exception as e:
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return f"An error occurred during web search: {str(e)}"
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# ---
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async def
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if not groq_key:
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return "\n\n--- ⚠️ Groq Summarization Skipped ---\nError: API Key is required.\nReturning raw text instead."
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try:
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current_date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
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if research_mode == 'deep':
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@@ -85,22 +85,18 @@ async def summarize_with_groq(text_to_summarize: str, query: str, groq_key: str,
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prompt_template = PROMPT_NORMAL
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prompt = prompt_template.format(query=query, context_text=text_to_summarize, current_date=current_date)
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messages=[{"role": "user", "content": prompt}],
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model=model_name,
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)
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return chat_completion.choices[0].message.content
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except Exception as e:
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return f"\n\n--- ⚠️
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# --- Main Orchestrator Function ---
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async def search_and_summarize(query, serper_api_key, search_type, num_results,
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scraped_text = await search_web_logic(query, serper_api_key, search_type, num_results)
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if
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summarized_text = await
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if "⚠️
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return scraped_text + summarized_text
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else:
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return summarized_text
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@@ -108,21 +104,24 @@ async def search_and_summarize(query, serper_api_key, search_type, num_results,
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# --- FastAPI App ---
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app = FastAPI()
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class SearchRequest(BaseModel):
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query: str
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serper_api_key: str
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search_type: str = "search"
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num_results: int = 4
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research_mode: str = "normal"
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@app.post("/api/search")
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async def api_search(request: SearchRequest):
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result = await search_and_summarize(
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request.query, request.serper_api_key, request.search_type, request.num_results,
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request.
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)
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return {"result": result}
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@@ -139,16 +138,16 @@ def create_gradio_app():
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search_type_input = gr.Radio(["search", "news"], value="search", label="Search Type")
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num_results_input = gr.Slider(1, 20, value=4, step=1, label="Number of Results")
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gr.Markdown("### Step 2: AI Summarization
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research_mode_input = gr.Radio(["normal", "deep"], value="normal", label="Research Mode", info="Normal for fast summary, Deep for detailed report.")
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search_button = gr.Button("Search & Summarize", variant="primary")
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output = gr.Textbox(label="Result", lines=25, max_lines=40)
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search_button.click(
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fn=search_and_summarize,
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inputs=[query_input, serper_api_key_input, search_type_input, num_results_input,
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outputs=output
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)
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with gr.Tab("Analytics"):
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from dateutil import parser as dateparser
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from fastapi import FastAPI
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from pydantic import BaseModel
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import google.generativeai as genai
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# <<< MISSING IMPORT ADDED BACK >>>
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from analytics import record_request, last_n_days_df, last_n_days_avg_time_df
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# --- Prompts ---
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except Exception as e:
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return f"An error occurred during web search: {str(e)}"
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# --- Gemini Summarization Logic ---
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async def summarize_with_gemini(text_to_summarize: str, query: str, gemini_key: str, model_name: str, research_mode: str) -> str:
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try:
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genai.configure(api_key=gemini_key)
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model = genai.GenerativeModel(model_name)
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current_date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
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if research_mode == 'deep':
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prompt_template = PROMPT_NORMAL
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prompt = prompt_template.format(query=query, context_text=text_to_summarize, current_date=current_date)
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response = await model.generate_content_async(prompt)
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return response.text
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except Exception as e:
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return f"\n\n--- ⚠️ Gemini Summarization Failed ---\nError: {str(e)}\nReturning raw text instead."
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# --- Main Orchestrator Function ---
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async def search_and_summarize(query, serper_api_key, search_type, num_results, gemini_api_key, gemini_model, research_mode):
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scraped_text = await search_web_logic(query, serper_api_key, search_type, num_results)
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if gemini_api_key and "Error:" not in scraped_text:
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summarized_text = await summarize_with_gemini(scraped_text, query, gemini_api_key, gemini_model, research_mode)
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if "⚠️ Gemini Summarization Failed" in summarized_text:
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return scraped_text + summarized_text
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else:
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return summarized_text
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# --- FastAPI App ---
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app = FastAPI()
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# Add CORS middleware if you plan to call the API from a different domain/frontend
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# from fastapi.middleware.cors import CORSMiddleware
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# app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
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class SearchRequest(BaseModel):
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query: str
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serper_api_key: str
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search_type: str = "search"
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num_results: int = 4
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gemini_api_key: Optional[str] = None
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gemini_model: Optional[str] = "gemini-2.5-flash-lite"
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research_mode: str = "normal"
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@app.post("/api/search")
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async def api_search(request: SearchRequest):
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result = await search_and_summarize(
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request.query, request.serper_api_key, request.search_type, request.num_results,
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request.gemini_api_key, request.gemini_model, request.research_mode
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)
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return {"result": result}
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search_type_input = gr.Radio(["search", "news"], value="search", label="Search Type")
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num_results_input = gr.Slider(1, 20, value=4, step=1, label="Number of Results")
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gr.Markdown("### Step 2: AI Summarization")
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research_mode_input = gr.Radio(["normal", "deep"], value="normal", label="Research Mode", info="Normal for fast summary, Deep for detailed report.")
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gemini_api_key_input = gr.Textbox(label="Your Gemini API Key", type="password", placeholder="Leave empty to skip summarization")
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gemini_model_input = gr.Textbox(label="Gemini Model", value="gemini-1.5-flash-latest")
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search_button = gr.Button("Search & Summarize", variant="primary")
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output = gr.Textbox(label="Result", lines=25, max_lines=40)
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search_button.click(
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fn=search_and_summarize,
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inputs=[query_input, serper_api_key_input, search_type_input, num_results_input, gemini_api_key_input, gemini_model_input, research_mode_input],
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outputs=output
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)
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with gr.Tab("Analytics"):
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requirements.txt
CHANGED
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@@ -1,3 +1,5 @@
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gradio
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httpx
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trafilatura
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@@ -6,4 +8,4 @@ limits
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filelock
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fastapi
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uvicorn
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-
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# requirements.txt
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gradio
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httpx
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trafilatura
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filelock
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fastapi
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uvicorn
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google-generativeai
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