update space

README.md

@@ -1,16 +1,145 @@
----
-title: Test
-emoji: 💬
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 5.42.0
-app_file: app.py
-pinned: false
-hf_oauth: true
-hf_oauth_scopes:
-- inference-api
-short_description: adfed
----
-
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+CRYPTO RAG CHATBOT - README
+=================================
+
+This is a cryptocurrency-focused Retrieval-Augmented Generation (RAG) app.
+It retrieves from your uploaded documents and added URLs, reranks results, and generates 
+answers with a chat LLM. It can also route "price" queries to a live price tool for major coins.
+
+1) OPENAI API KEY (REQUIRED; PASTE-ONLY, NEVER SAVED)
+-----------------------------------------------------
+- The chat model requires an OpenAI API key.
+- Paste your key into the "OpenAI API Key" field in the UI.
+- The key is kept in memory for the current session only:
+  - It is not written to disk, not bundled in the repository, and not logged.
+  - Restarting or refreshing the Space clears it.
+- The key is used only to generate chat responses for this app.
+
+2) QUICK COST ESTIMATE (GPT-4o-mini PRICING)
+--------------------------------------------
+Pricing used: (https://platform.openai.com/docs/pricing)
+- Input:  $0.15 per 1,000,000 tokens
+- Output: $0.60 per 1,000,000 tokens
+
+Assumptions:
+- 200 input tokens per query
+- 500 output tokens per query
+- 20 queries total
+
+Per-query cost:
+- Input:  200 / 1,000,000 * $0.15 = $0.00003
+- Output: 500 / 1,000,000 * $0.60 = $0.00030
+- Total per query = $0.00003 + $0.00030 = $0.00033
+
+20-query session:
+- $0.00033 * 20 = $0.0066
+
+Result: Approximately six-tenths of a cent ($0.0066) for the full try, well under the $0.50 budget.
+
+3) FREE OPEN-SOURCE RETRIEVAL MODELS
+------------------------------------
+- Embeddings: sentence-transformers/all-MiniLM-L6-v2
+- Reranker:   cross-encoder/ms-marco-MiniLM-L-6-v2
+These run locally in the Space and are free (no API costs).
+
+4) UPLOADING .PDF / .TXT / .MD FILES (FOR RAG)
+----------------------------------------------
+- Click "Add files" and select any combination of .pdf, .txt, or .md.
+- The app extracts text (PDFs via pypdf), splits into chunks, and stores them
+  with metadata for retrieval.
+- After adding files, click "Build Index" so they are included in search.
+
+5) ADDING MULTIPLE URLS (FOR RAG)
+---------------------------------
+- Paste one URL per line in the "URLs" box and click "Add URLs".
+- The app fetches and parses the pages (static articles and PDFs work best).
+- After adding URLs, click "Build Index" to include them in retrieval.
+
+6) BUILD INDEX AND RETRIEVAL OPTIONS
+------------------------------------
+After you add files and/or URLs, click "Build Index". You can tune:
+
+- Top-K retrieve (k): how many candidates to pull initially (e.g., 6 to 10).
+- Hybrid alpha (BM25 <-> Dense): blend between keyword BM25 and dense
+  similarity. 0.0 = all dense, 1.0 = all BM25. A balanced default is 0.5.
+- Rerank Top-K: how many of the retrieved candidates the cross-encoder reranks
+  (e.g., 3 to 8). The final answer uses the top reranked passages.
+
+If results seem off:
+- Increase Top-K for better recall.
+- Adjust alpha (higher favors keywords; lower favors semantic similarity).
+- Increase Rerank Top-K for stronger final ordering (slightly more CPU).
+
+7) STREAMING RESPONSES (SELECTABLE)
+---------------------------------
+- Streaming ON: words appear live as the model generates. 
+- Streaming OFF: you receive a single final answer after generation finishes.
+Toggle this with the "Streaming" checkbox.
+
+8) CHAT MODEL CHOICE (FIXED FOR NOW)
+------------------------------------
+- The chat model is fixed in this version of the app for reliability and cost
+  control. If you need a different model, it can be changed in code and
+  redeployed; the UI currently does not expose a model selector.
+
+9) LIVE PRICE SEARCH FOR MAJOR COINS + ROUTING
+----------------------------------------------
+- If your question looks like a price query (for example: "BTC price",
+  "price of ETH", "SOL price in USD"), the app routes to a tool instead of RAG:
+  - It calls a public price API (for example, CoinGecko) to get the latest
+    price for major coins such as BTC, ETH, SOL, and XRP.
+  - It can also show the Fear and Greed Index for market sentiment.
+- Routing logic: the pipeline checks your query for price-intent keywords
+  ("price", "quote", "market cap", "ATH", and similar). If matched, it uses
+  the tools route; otherwise it uses the RAG route (retrieve -> rerank -> answer).
+
+10) QUICK START
+---------------
+1. Initialize pipeline (if manual init is enabled).
+2. Paste your OpenAI API key (not saved).
+3. Add files and/or add URLs.
+4. Click Build Index.
+5. Ask questions. E.g. "what is Ethereum vs Solana?", "What is bitcoin strength and weakness?"
+6. For prices, try queries like "ETH price", "SOL quote", "XRP price in USD".
+
+NOTES
+-----
+- This tool is for research and education only. It is not financial advice.
+- For best results, use focused, well-structured documents and reputable URLs.
+
+
+
+### Installation and Execution (for Gradio UI)
+---------------
+1. **Create a new Python environment:**
+
+   ```bash
+   python -m venv .venv
+   ```
+
+2. **Activate the environment:**
+
+   For macOS and Linux:
+
+   ```bash
+   source .venv/bin/activate
+   ```
+
+   For Windows:
+
+   ```bash
+   .venv\Scripts\activate
+   ```
+
+3. **Install the dependencies:**
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. **Run the application:**
+
+   ```bash
+   python app.py
+   ```
+
+